Tesis sobre el tema "Predictive motor control"

Although human sustained control movements are continuous in nature there is still controversy on the mechanisms underlying such physiological systems. A popular topic of debate is whether human motor control mechanisms could be modelled as engineering control systems, and if so, what control algorithm is most appropriate. Since the early years of modelling sustained control tasks in human motor control the servomechanism has been an adequate model to describe human tracking tasks. Another continuous-time system model that is often used to model sustained control tasks is the predictive controller which is based on internal models and includes prediction and optimisation. On the other hand, studies have suggested intermittent behaviour of the ``human controller'' in sustained motor control tasks. This thesis investigated whether intermittent control is a suitable approach to describe sustained human motor control. It was investigated how well an intermittent control system model could approximate both the deterministic and non-deterministic parts of experimental data, from a visual-manual compensatory tracking task. Finally, a preliminary study was conducted to explore issues associated with the practical implementation of the intermittent control model. To fit the deterministic part of experimental data, a frequency domain identification method was used. Identification results obtained with an intermittent controller were compared against the results using continuous-time non-predictive and predictive controllers. The results show that the identified frequency response functions of the intermittent control model not only fit the frequency response functions derived from the experimental data well, but most importantly resulted in identified controller parameters which are similar to those identified using a predictive controller, and whose parameter values appear to be physiologically meaningful. A novel way to explain human variability, as represented by the non-deterministic part of the experimental data (the \emph{remnant}), was developed, based on an intermittent control model with variable intermittent interval. This model was compared against the established paradigm, in which variability is explained by a predictive controller with added noise, either signal dependent control signal noise, or observation noise. The study has shown that the intermittent controller with a variable intermittent interval could model the non-deterministic experimental data as well as the predictive controller model with added noise. This provides a new explanation for the source of remnant in human control as inherent to the controller structure, rather than as a noise signal, and enables a new interpretation for the physiological basis for human variability. Finally, the theoretical intermittent control model was implemented in real-time in the context of the physiological control mechanism of human standing balance. An experimental method was developed to apply automatic artificial balance of an inverted pendulum in the context of human standing, via functions electrical stimulation control of the lower leg muscles of a healthy subject. The significance of this study is, firstly, that frequency domain identification was applied for the first time with intermittent control, and it could be shown that both intermittent and predictive control models can model deterministic experimental data from manual tracking tasks equally well. Secondly, for the first time the inherent variability, which is represented by the remnant signal, in human motor control tasks could be modelled as part of the structure of the intermittent controller rather than as an added noise model. Although, the experimental method to apply automatic artificial balance of an inverted pendulum in the context of human standing was not successful, the intermittent controller was implemented for the first time in real-time and combined with electrical muscle stimulation to control a physiological mechanism.

Induction machine drives with various configurations are getting a lot of attention in several industrial applications. Due to this increasing demand in industrial applications, the significance of developing effective control approaches for obtaining a high dynamic performance from the induction machine drives became essential. Up to the present time, the control of induction machine drives using power converters has been based on the principle of mean value, using pulse width modulation with linear controllers in a cascaded structure. Recent research works have demonstrated that it is possible to use Predictive Control to control induction machine drives with the use of power converters, without using modulators and linear controllers. This new approach will have a strong impact on control in power electronics in coming decades. The advantages of Predictive Control are noticed through the ability to consider a multi-objective case within the model, easy inclusion of non-linearities within the model, simple treatment of system constraints, easy of digital implementation, and flexibility of including modifications and extension of control horizons according to the required applications. Upon this, the research presented in this thesis concerns with developing different control topologies for various configurations of induction machine drives based on finite control set model predictive control (FCS-MPC) principle, which actuates directly the switch states of the voltage source inverter (VSI). In addition, for enhancing the robustness of the induction machine drives, different sensorless approaches are utilized and tested for validations. The first topology of induction machine drives that has been studied is the induction motor (IM) drive. An effective model predictive direct torque control (MP DTC) approach is used to control the torque and stator flux of the motor through the utilization of an effective cost function, through which the understanding and comparing implementation variants and studying convergence and stability issues can be easily investigated. The speed sample effect on the control variants and overall performance of the proposed MP DTC is analyzed, which enables the understanding of the real base principle of DTC, as well as why and when it works well. Two different sensorless procedures for estimating the speed and rotor position are used by the proposed MP DTC approach; the first utilizes a model reference adaptive system (MRAS) observer, while the other exploits the prediction step during the implementation of proposed MP DTC to get the speed information through performing a linear extrapolation of the speed values starting from the last two estimated samples. Extensive simulation and experimental tests have been carried out to validate the effectiveness of both sensorless approaches in achieving precise tracking of speed commands for a wide range of variations. For enhancing the robustness of proposed MP DTC, the stator flux as a control variable is replaced with controlling the flow of the reactive power through the induction motor drive. As the reactive power is a measured quantity compared with the estimated value of stator flux, thus, the sensitivity of the control against parameters variation is limited, and this confirmed through the obtained results from both simulation and experimental tests. In addition, an effective alternative approach to the MP DTC is presented, which based on controlling the instantaneous values of the active and reactive powers of the IM drive based on model predictive principle, instead of controlling the torque and flux as in MP DTC. This technique has the advantage that all controlled variables are became measured quantities (active and reactive powers), thus the estimation problems that commonly present in classic DTC schemes are effectively limited. For the last two control approaches (MP DTC reactive power control, and MP IPCactive and reactive power control), the sensorless that utilizes the predictive feature is also adopted. Obtained results via simulation and experiments confirm the feasibility of the two alternatives control procedures in obtaining a robust dynamic response of IM drive. To limit the accompanied ripple contents in the controlled values of electromagnetic torque and stator flux of induction motor, an effective ripple reduction technique has been presented. The technique is based on the derivation of the optimal value for the weighting factor (w_f) used in the cost function. A detailed mathematical derivation of the optimal value of w_f is introduced based on the analysis of torque and flux ripples behaviors. The proposed ripple reduction technique has been validated via simulation utilizing Matlab/Simulink software, and experimentally tested using a fast control prototyping dSpace 1104 board. In addition, the prediction step based sensorless approach is adopted during implementation. The performance of the IM drive using the proposed approach is compared with the results obtained from MP DTC approach that uses an arbitrary value of w_f. The comparison confirms the validity of the proposed ripple reduction procedure in reducing the ripple contents in the controlled variables while preserving the permissible computation burdens during the implementation. The FCS-MPC principle is also utilized to control the current of induction motor as an alternative to classic field oriented control (FOC), the proposed model predictive current control (MPCC) approach belongs to the class of the hysteresis predictive control (for limiting the switching frequency) as the MPCC is triggered by the exceeding of the error of a given threshold. In addition, a sensorless drive is achieved by including an effective Luenberger observer (LO) for precise estimation of rotor flux vector together with stator current, speed and load torque. The stator currents are estimated to eliminate the accompanied noise in their values when they are directly measured, thus the currents noise during prediction is limited. An effective pole placement procedure for the selection of observer gains has been adopted. The procedure is based on shifting the poles of the observer to the left of the motor poles in the complex (s-plane) with low imaginary part, so that the stability of the observer is enhanced for wide speed range. The feasibility of the sensorless MPCC for IM drive is confirmed through the obtained simulation and experimental results. The second topology of induction machine drives that has been studied is the doubly fed induction motor (DFIM) drive. An effective model predictive direct torque control (MP DTC) algorithm is developed for controlling the torque and rotor flux of DFIM drive. In addition, an effective sensorless approach is presented, which estimates the speed and rotor position in an explicit way without the need for involving the flux in the estimation process, thus the effect of parameters variation on the overall performance of the sensorless observer is effectively limited, this has been approved through the obtained results that are performed for a wide speed range from sub-synchronous to super-synchronous speed operation. During the operation, the stator resistance and magnetizing inductance values are changed from their original values to study the variation effect on the observer performance. Matlab/Simulink software and a prototyping dSpace 1104 control board are used to validate the effectiveness of proposed sensorless MP DTC approach through simulation and experiments, respectively. The results proof the robustness of the proposed sensorless approach and its ability to achieve precise estimation of the speed and rotor position. The third topology of induction machine drives that has been studied is the doubly fed induction generator (DFIG). A detailed analytical derivation for the proposed model predictive direct power control (MP DPC) approach for DFIG is presented, which as a sequence considered as a transposed control approach from the MP DTC used before for doubly fed induction motor (DFIM). A sensorless approach based on model reference adaptive system (MRAS) observer is adopted for estimating the speed and rotor position. Both simulation using Matlab/Simulink software and experimental test using a prototyping dSpace 1104 control board have tested the dynamic performance of the drive. Obtained results affirm the feasibility of the proposed MP DPC approach in achieving a decoupled control of active and reactive powers for DFIG. In summary, it can be said that the proposed model predictive control approaches have proved their ability in achieving high dynamic performance for different topologies of induction machine drives. In addition, the proposed sensorless techniques have confirmed their effectiveness for a wide range of speed variations. All of this are approved and validated through extensive simulation and experimental tests.
Gli azionamenti con machine ad induzione (macchine asincrone nelle loro varie configurazioni), stanno riacquistando molta attenzione in diverse applicazioni industriali. A causa di questo crescente interesse applicativo, è diventato di essenziale importanza lo sviluppo di efficaci tecniche di controllo per ottenere dagli azionamenti in questione elevate prestazioni dinamiche. Fino ad oggi, il controllo degli azionamenti con macchina a induzione alimentati da convertitori di potenza è basato sul “principio del valore medio” delle grandezze in commutazione, utilizzando la modulazione di larghezza di impulsi con controllori lineari in una struttura a cascata. Recenti ricerche hanno dimostrato che è possibile utilizzare il Controllo Predittivo per controllare gli azionamenti con macchina a induzione, con l'utilizzo di convertitori di potenza senza utilizzare modulatori e controllori lineari. Questo nuovo approccio avrà un forte impatto sul controllo dell'elettronica di potenza nei prossimi decenni. I vantaggi del Controllo Predittivo derivano dalla possibilità di perseguire problemi multi-obiettivo, di includere facile le non linearità all'interno del modello, di trattare in modo semplice i vincoli di sistema, nonché dalla facilità di implementazione digitale e dalla flessibilità di includere modifiche ed estensioni al controllo secondo le applicazioni richieste. Inlinea con tutto ciò, la ricerca presentata in questa tesi riguarda lo sviluppo di diverse topologie di controllo per varie configurazioni di azionamenti con macchine a induzione, basate sul principio di Controllo Predittivo a modello con insieme finito degli stati di controllo (Finite Control Set Model Predictive Control - FCS-MPC), che definisce direttamente l’assetto dell'inverter di tensione (VSI). Inoltre, per aumentare la robustezza degli azionamenti, vengono proposti e sperimentati diversi approcci senza sensori elettromeccanici (sensorless). La prima topologia studiata di azionamenti con macchina a induzione (IM) è l'azionamento con motore a gabbia. Il controllo diretto di coppia (DTC) è aggiornato in termini di controllo predittivo a modello (MP DTC) e usato per controllare la coppia e il flusso statorico attraverso l'utilizzo di una efficace funzione di costo attraverso la quale è anche possibile facilmente comprendere e confrontare le varianti di implementazione e studiare i problemi di convergenza e di stabilità. Viene analizzato l'effetto della velocità sulle diverse versioni di controllo e sulle prestazioni complessive del MP DTC proposto; ciò consente di comprendere appieno il principio del DTC, nonché perché e quando esso funzioni bene. Vengono utilizzate due diverse procedure di stima della posizione e della velocità del rotore nel MP DTC proposto; il primo utilizza uno stimatore adattivo con modello di riferimento (MRAS), mentre l'altro sfrutta la stessa fase di predizione del MP DTC proposto per ottenere le informazioni sulla velocità effettuando infine un'estrapolazione lineare dei valori di velocità a partire dagli ultimi due campioni stimati. Sono state eseguite numerose prove in simulazione e sperimentali per convalidare l'efficacia di entrambi gli approcci sensorless nell’ottenere un preciso inseguimento del comando di velocità per una vasta gamma di situazioni. Per migliorare la robustezza del MP DTC proposto rispetto alle variazioni parametriche, il controllo del flusso dello statore viene sostituito con quello della potenza reattiva assorbita dal motore ad induzione; di conseguenza la sensibilità del controllo alle variazioni dei parametri è limitata e ciò è confermato attraverso i risultati ottenuti sia dalla simulazione che dalle prove sperimentali. Inoltre, viene presentato un ulteriore efficace approccio alternativo per il MP DTC, basato sul principio del controllo predittivo a modello dei valori istantanei delle potenze attive e reattive dell'azionamento, invece di controllare la coppia e il flusso come nell’usuale MP DTC. Questa variante ha il vantaggio che tutte le variabili controllate sono divenute quantità misurate (potenze attive e reattive) e quindi i problemi di stima comunemente presenti nei classici schemi DTC sono efficacemente limitati. Per gli ultimi due approcci di controllo (controllo di coppia e di potenza reattiva e controllo di potenza attiva e reattiva) viene anche adottato la stima della velocità rotorica che sfrutta la funzione predittiva del controllo. I risultati ottenuti attraverso la simulazione e la sperimentazione confermano la fattibilità delle due procedure alternative di controllo per ottenere una risposta dinamica robusta dell’azionamento con IM. Per limitare il ripple che accompagna gli andamenti controllati della coppia e del flusso statorico del motore, è stata presentata una tecnica efficace di riduzione della sua ampiezza. La tecnica è basata sull’impiego di un valore ottimale per il fattore di ponderazione w_f utilizzato nella funzione di costo per sommare i due contributi che la definiscono. Viene introdotta una derivazione matematica dettagliata del valore ottimale di w_f attraverso l'analisi dei comportamenti dell’ondulazione di coppia e del flusso. La tecnica di riduzione del ripple proposta è stata verificata tramite la simulazione usando il software Matlab/Simulink e sperimentalmente utilizzando la scheda di rapida prototipazione del controllo dSpace 1104. Ancora, l'implementazione adotta l'approccio sensorless basato sulla fase di predizione. Le prestazioni dell’azionamento con IM utilizzando quest’ultimo approccio proposto sono confrontate con i risultati ottenuti con l'approccio MP DTC che utilizza invece un valore arbitrario di w_f. Il confronto conferma la validità della procedura di riduzione del ripple nelle variabili controllate mantenendo nel contempo gli oneri di calcolo entro i limiti consentiti per l'implementazione. Il principio FCS-MPC è anche utilizzato per controllare la corrente del motore di induzione come alternativa al controllo classico ad orientamento di campo (Field Oriented Control -FOC). L'approccio proposto di controllo di corrente di tipo predittivo (Model Predictive Current Control - MPCC) appartiene alla classe del controllo predittivo ad isteresi (per limitare il frequenza di commutazione) in quanto il MPCC viene attivato dal raggiungimento dell’errore di corrente di una determinata soglia. In questo caso, la caratteristica sensorless dell’azionamento è ottenuta includendo un efficace osservatore Luenberger (LO) per una precisa stima del vettore del flusso del rotore insieme alla coppia di carico e alla velocità. È stata adottata una efficace procedura di allocazione dei poli per la selezione dei guadagni dell'osservatore; la procedura si basa sul posizionamento dei poli dell'osservatore a sinistra di quelli del motore nel complesso (piano di s) con una ridotta parte immaginaria, in modo che la stabilità dell'osservatore sia migliorata in un'ampia gamma di velocità. La fattibilità dell'azionamento sensorless con MPCC è ancora confermata attraverso la simulazione e i risultati sperimentali. La seconda topologia degli azionamenti con macchina a induzione che è stata studiata è l'azionamento con motore ad anelli con rotore alimentato da invertitore e statore da rete (Doubly Fed Induction Motor DFIM). È stato sviluppato un efficace algoritmo predittivo a modello (MP DTC) per il controllo dinamico della coppia e del flusso di rotore dell'azionamento DFIM. Inoltre, viene presentato un approccio efficace di soluzione sensorless che valuta la velocità e la posizione del rotore in modo esplicito senza la necessità di coinvolgere la stima del flusso nel processo di predizione; di conseguenza l'effetto delle variazioni dei parametri sulle prestazioni complessive dell'osservatore di posizione e velocità è sensibilmente limitato. Questo è stato provato attraverso i risultati ottenuti con test eseguiti in un'ampia gamma di velocità, dal sub-sincronismo a velocità super-sincrona. Durante l'operazione, la resistenza dello statore e i valori di induttanza di magnetizzazione sono stati modificati rispetto ai valori reali per studiare l'effetto di variazioni parametriche sulle prestazioni dell'osservatore. Anche in questo caso, il software Matlab/Simulink e una scheda di controllo dSpace 1104 sono stati utilizzati per convalidare l'efficacia dell'approccio sensorless del MP DTC per l’azionamento. I risultati dimostrano la robustezza del controllo sensorless proposto e la sua capacità di ottenere una precisa stima della posizione e della velocità del rotore. La terza topologia di azionamenti con macchina a induzione che è stata studiata è quella del generatore ad induzione con rotore avvolto (DFIG) e invertitore sul rotore. Viene presentata una derivazione analitica dettagliata del controllo predittivo diretto di potenza (MP DPC) per DFIG, che trasferisce ed estende l’approccio di controllo del MP DTC citato prima per il motore a induzione a doppia alimentazione (DFIM). Una soluzione sensorless ancora basata sull'osservatore adattivo a modello di riferimento (MRAS) è adottato per stimare la velocità e la posizione del rotore. Sia le simulazioni usando il software Matlab/Simulink che i test sperimentali utilizzando la scheda dSpace 1104 hanno mostrato le elevate prestazioni dinamiche dell'azionamento. I risultati ottenuti confermano la fattibilità del metodo MP DPC proposto per ottenere un controllo disaccoppiato di potenze attive e reattive per DFIG. In sintesi, si può dire che l'utilizzo proposto del controllo predittivo a modello ha dimostrato la sua capacità di ottenere elevate prestazioni dinamiche per le diverse topologie degli azionamenti con macchina ad induzione considerati. Inoltre, le tecniche sensorless proposte hanno confermato la loro efficacia per una vasta gamma di velocità. Tutto questo è stato verificato e validato attraverso una vasta attività analisi simulativa e di sperimentazione in laboratorio.

A causa delle alte frequenze di campionamento e delle ridotte risorse computazionali, la certificazione di complessità ha un ruolo chiave nella determinazione del successo del Model Predictive Control (MPC) nelle applicazioni embedded. Questa tesi propone un algoritmo di certificazione per metodi active-set duali, che permette di calcolare esattamente il tempo massimo di risoluzione di un problema di Quadratic Programming (QP) parametrico, risultante ad esempio da formulazioni MPC lineari. Dato un problema MPC e una piattaforma di calcolo è quindi possibile certificare se il problema di ottimizzazione sarà sempre risolto nel limite di tempo. La mancanza di una certificazione è anche una minaccia per la validità dei metodi di accelerazione, dato che il miglioramento del tempo massimo di soluzione è molto più importante di quello medio per embedded MPC. Due nuovi metodi sono presentati per i quali il miglioramento nel caso peggiore è certificabile esattamente. Il primo è un MPC semi-esplicito che combina un risolutore online con la legge multiparametrica delle partizioni poliedrali che incidono maggiormente sul caso peggiore. Il secondo consiste in una selezione alternativa dei vincoli violati per metodi active-set duali, la quale diminuisce sia il numero massimo di iterazioni, sia la complessità della singola iterazione. Infine, la tesi propone applicazioni sperimentali di embedded MPC a motori elettrici e convertitori di potenza. Il controllo di coppia di un motore brushless tramite MPC è validato su un’unità di controllo economica, risultando più veloce della corrispondente soluzione multiparametrica. Viene poi presentato un controllo MPC per convertitori DC-DC pre-compensati per aggirare il problema dei controllori primali non modificabili. Inoltre, è affrontato il problema della stima dello stato per diversi convertitori nella stessa unità di alimentazione, sviluppando un osservatore robusto e non lineare unificato per sei diverse tipologie di convertitori.
Due to the fast sampling frequency and the scarce computational resources, the complexity certification of optimization algorithms plays a key role in determining the success of embedded Model Predictive Control (MPC). This thesis proposes a certification algorithm for dual active-set methods, able to compute exactly the worst-case number of iterations and the amount of time needed to solve a parametric Quadratic Programming (QP) problem, like those that arise in linear MPC. Therefore, given an MPC problem and a computational unit, it can be certified if the optimization problem will be always solved in the prescribed amount of time. The lack of a complexity certification is a threat for accelerating methods as well, as speeding up the worst-case time is much more important than improving the average case in embedded MPC. The thesis presents two novel accelerating methodologies, for which the worst-case improvement can be exactly certified. The first is a semi-explicit MPC, combining an online solver with the multiparametric solution of those polyhedral regions that most affect the worst-case time. The second method consists of an alternative selection for violated constraints in dual active-set solvers, which lowers the worst-case number of iterations and the complexity of the single iteration. Finally, embedded MPC for electrical drives and power converters is experimentally investigated. MPC for the torque control of a brushless motor is demonstrated to be feasible on a cheap control board, and even faster than the corresponding multiparametric solution. Embedded MPC for pre-compensated DC-DC converters is developed, in order to overcome the obstacle of a non-modifiable primal controller, very common in power converters. The issue of estimating the state for multiple DC-DC converters on the same power supply is also addressed, by presenting a unified nonlinear robust observer for six different converter topologies.

Orientador: Edson Bim
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: Uma abordagem preditiva global-local para o controle de um motor de indução é apresentado nesta tese. O conceito de controle preditivo diz respeito a uma classe de controladores que tem se desenvolvido muito no âmbito do controle de sistemas de conversão de energia nos últimos anos, acompanhando o desenvolvimento da capacidade computacional dos sistemas microprocessados ao longo da última década. A técnica proposta é fundamentada numa lei de controle baseada em uin modelo identificado de um motor de indução. A identificação se dá de maneira experimental a partir da simulação de um motor de indução indiretamente orientado em função do fluxo do rotor, através de um modelo fuzzy do tipo Takagi-Sugeno TS com Funções de Base Ortonormal no consequente das regras.As ações de controle locais são combinadas são combinadas pela ativação das regras do modelo local devido, e a ação de controle global resultante é aplicada ao controle de velocidade do motor de indução. Este método permite ao controlador a inclusão nos parâmetros de controle das não-linearidades e restrições inerentes ao controle do máquinas elétricas
Abstract: A predictive global-local approach technic for induction motor control is presented in this thesis. Predictive control is a very wide class of controllers that have found rather recent applications in the control of electrical machines. Research on this topic has been increased in the last years due to the possibilities of today s microprocessors used for control. The proposed technique is founded on a identified model based predictive control. The identification technique applied in this method is based on the black box modeling of a Indirect Rotor Flux Oriented Induction Motor in stationary reference system through Takagi-Sugeno-TS fuzzy models with orthonormal base functions - OBF - on the rules consequents. Control actions are matched by local activation of the model rule because local and global control action is applied to speed control of an induction motor. This method allows the inclusion in the control parameters of non-linearities and constraints inherent the control of electrical machines
Mestrado
Energia Eletrica
Mestre em Engenharia Elétrica

Le problème de commande motrice de systèmes exécutant des activités multi-objectifs et fortement contraintes est à résoudre pour permettre l’émergence de comportements performants et robustes ; l’élaboration de stratégies complexes de coordination motrice est critique pour en assurer les performances, faisabilité et sécurité.Bien que les approches de commande prédictive multi-objectifs permettent la définition de stratégies complexes et sous contraintes coordonnant l’activité motrice du système, leur coût de calcul est un inconvénient critique à leur application.Le travail présenté dans ce manuscrit vise à considérer des techniques de commande prédictive multi-objectifs pour des applications pratiques à la robotique humanoïde.Une architecture de commande est alors proposée sous la forme d’un contrôleur multi-objectif à deux niveaux, exploitant les avantages respectifs des formulations prédictive et instantanée.La contribution de ce travail prend la forme de la validation des avantages d’une telle approche dans son développement pour des défis pratiques, en simulation et implémentation temps-réel, sur les robots iCub et TORO ainsi que sur des modèles d’humain.Le coût de calcul du niveau prédictif est contenu par l’introduction de problèmes réduits, permettant la formulation avantageuse de problèmes de commande au travers de programmes en nombres entiers mixtes et de distributions séquentielles et parallèles.Malgré les approximations sur la dynamique du système au niveau prédictif, des comportements complexes émergent, exploitant des stratégies de coordination entre objectifs et contraintes conflictuels pour augmenter les performances et robustesse face à des perturbations
Rising to the challenge of motor control for systems involved in multi-objective and highly-constrained activities is a requirement to enable the emergence of efficient and robust behaviors; the elaboration of complex motor coordination strategies is critical in ensuring performance, feasibility and safety.Although multi-objective predictive approaches enable the definition of complex and constrained strategies coordinating the motor activity of the system, their computational cost is a critical drawback from practical applications.The work presented in this dissertation aims at considering multi-objective predictive control for feasible and practical applications to humanoid robotics.A control architecture is proposed to this purpose as a multi-objective, two-layered controller exploiting the respective advantages of predictive and instantaneous formulations.The contribution of this work takes the form of the validation of the benefits from such an approach in its development for practical challenges and applications, in simulation and real-time implementation, on the iCub and TORO robots and virtual human models.Computational demand of the predictive level is contained with the introduction of reduced multi-objective predictive problems, enabling computationally-favorable formulations of the control problem using mixed-integer programming and sequential and parallel distributions.Despite the resulting approximations on the dynamics of the system at the predictive level, complex behaviors are emerging, exploiting elaborate coordination strategies between conflicting objectives and constraints to increase performance and robustness against disturbances

This thesis focuses on the possibilities of application of nonlinear model predictive control for electric drives. Specifically, for drives with a permanent magnet synchronous motor. The thesis briefly describes the properties of this type of drive and presents its mathematical model. After that, a nonlinear model of predictive control and methods of nonlinear optimization, which form the basis for the controller output calculation, are described. As it is used in the proposed algorithm, the Active set method is described in more detail. The thesis also includes simulation experiments focusing on the choice of the objective function on the ability to control the drive. The same effect is examined for the different choices of the length of the prediction horizon. The end of the thesis is dedicated to the comparison between the proposed algorithm and commonly used field oriented control. The computational demands of the proposed algorithm are also measured and compared to the used sampling time.

Thesis (M.S.)--University of Nevada, Reno, 2007.
"August, 2007." Includes foldout illustrations. Includes bibliographical references (leaves 79-84). Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2008]. 1 microfilm reel ; 35 mm. Online version available on the World Wide Web.

This text focuses on advanced torque control of permanent magnet synchronous motor drives. A novel modular structure is introduced to simplify the design and implementation of Model Predictive Control (MPC). The layout consists of the control and the control framework. The dynamic control is the novel virtual flux controller, which is used to reach desired reference values, and the state observer, which is used to reduce effects of non-modeled system properties. The control framework consists of static mappings to simplify the control problem. Besides the alpha-beta and d-q transformations, a reference generation procedure is used to generate state references based on optimality criteria. Also, the actuation scheme is part of the control framework and defines the available input set and the resulting control properties. The first method actuates directly switch states, i.e. voltage vectors, which yield an integer set named Finite Control Set (FCS). The other method actuates duty cycles via modulation, which yield the Convex Control Set (CCS). A stability analysis is carried out for both, CCS-MPC and FCS-MPC. MPC is called stable, if it is feasible and convergent, which can be ensured using the main MPC stability theorem. However, stringent computation requirements make it difficult to apply the theorem in practice. Thus, the Lyapunov based MPC approach is applied to the motor drive, which provides stability guarantees independent of the prediction horizon. A stability constraint based on control Lyapunov functions (CLF) ensures convergence to the origin and the resulting optimal control problem is shown to be feasible for all time. In other words, a control input can be found at each sampling instant, which satisfies all constraints and yields a stable closed-loop system. The properties of CCS-MPC are derived using a nonlinear controller and the constrained closed-loop system is shown to be stable in the sense of Lyapunov. The stability properties of FCS-MPC are more complex due to the integer input set. Using set-theoretical methods, it is shown that a sufficiently large control error can be steered towards the origin. In other words, the proposed FCS-MPC is shown to be set stable, i.e. the control error is guaranteed to converge to a well-defined neighborhood of the origin. MPC requires that a Constrained Finite Time Optimal Control (CFTOC) problem is solved at each sampling time. Small sampling periods and limited computation capabilities of embedded hardware require the CFTOC to be sufficiently simple, which is achieved using the virtual flux model in the static reference frame. The problem size is contained using a sufficiently small prediction horizon and efficient algorithms are necessary to provide a result within a sampling period. The CFTOC of the proposed CCS-MPC is a (convex) linear or quadratic programming problem, which can be solved using existing efficient algorithms. To provide a minimal approach, an efficient algorithm is introduced to solve the one-step-ahead prediction CFTOC analytically. FCS-MPC results in a mixed integer programming problem and is therefore more difficult to solve with standard numerical methods. In practice, the CFTOC is solved by enumeration, which is combined with branch-and-bound, i.e. branch-and-cut, techniques to improve the computational efficiency. The control algorithms have been developed on a Software-in-the-Loop (SiL) platform based on Matlab/Simulink and the code is implemented without modification on an experimental test-bench. The evaluation confirms the design and implementation of CCS-MPC and FCS-MPC and shows good results in dynamic and steady-state operation. The two MPC approaches have complimentary properties, which can be used to target different applications. CCS-MPC achieves a constant switching frequency and is a promising alternative to proportional-integral (PI) vector control. The concept can be combined with different modulation schemes, e.g. the Symmetric Space Vector Modulation (SSVM) and the Discontinuous Space Vector Modulation (DSVM) are used in this text. FCS-MPC takes the inverter switching into account and achieves an approximately constant switching ripple but a variable switching frequency. The concept is most profitably applied to systems where a high sampling frequency compared to the switching frequency is desired, e.g. high power or servo drives. Moreover, FCS-MPC lacks Pulse Width Modulation (PWM) harmonics in its current spectrum. Consequently, it is advantageous in terms of acoustic noise since emphasized tones are missing. However, the distinguished PWM harmonics of CCS-MPC are simpler to filter. In summary, it can be said that the work on advanced torque control of permanent magnet synchronous motor drives has produced an innovative strategy. The introduction of a new structure has significantly simplified the model predictive control problem, the concept of stability in particular. Moreover, this structure results in the implementation of simple algorithms, which can be computed efficiently.
Il soggetto affrontato dal presente lavoro sono i controlli avanzati di coppia per azionamenti con un motore sincrono a magneti permanenti. A questo scopo, è stata introdotta una struttura modulare che semplifica la progettazione e l’implementazione del controllo predittivo basato su un modello (model predictive control, MPC): lo schema è costituito dal controllo dinamico e dal quadro di controllo. Il controllo dinamico è un regolatore di flusso virtuale, utilizzato per raggiungere un valore di riferimento voluto e un osservatore di stato che serve a ridurre gli effetti delle proprietà non modellizzate del sistema. Il problema del controllo è stato semplificato tramite l’utilizzo di trasformate statiche chiamate quadro di controllo. Accanto alle trasformate alpha-beta e d-q viene usata una procedura per la generazione di riferimenti di stato, basati su un criterio ottimale. Il quadro di controllo contiene anche lo schema di attuazione, che serve per definire l’insieme di ingressi disponibili. Da un lato, il controllore comanda in modo diretto l’accensione e lo spegnimento dei semiconduttori, ovvero i vettori di tensione, ottenendo un insieme finito d’ingressi (Finite Control Set, FCS). Dall’altro lato vengono attuati cicli di accensione (duty-cycles) attraverso una modulazione (pulse width modulation, PWM): ciò risulta in un insieme convesso d’ingressi (convex control set, CCS). È stata eseguita un’analisi di stabilità sia per CCS-MPC sia per FCS-MPC. MPC è stabile, se il problema di controllo ottimale ad esso associato è risolvibile e l’errore di stato converge all’origine. Tale stabilità può essere garantita attraverso il principale teorema di stabilità di MPC. Tuttavia, i requisiti di calcolo restrittivi rendono il teorema difficilmente applicabile nella pratica. Di conseguenza, viene introdotto l’approccio MPC basato su Lyapunov (Lyapunov-based MPC) per gli azionamenti, il quale fornisce garanzie sulla stabilità indipendentemente dall’orizzonte di predizione. Un vincolo di stabilità basato sulle funzioni di controllo di Lyapunov (control Lyapunov function, CLF) assicura la convergenza all’origine ed è stato provato che il problema ottimale di controllo risultante è sempre risolvibile. In altre parole, ad ogni istante di campionamento si può trovare un ingresso che soddisfi tutti i vincoli del sistema e renda stabile il sistema a circuito chiuso. Le proprietà di CCS-MPC vengono ottenute utilizzando un controllo non lineare ed è dimostrato che il sistema vincolato ad anello chiuso è stabile secondo Lyapunov. Le proprietà di stabilità di FCS-MPC sono più complesse a causa dell’insieme non continuo d’ingressi. Utilizzando metodi della teoria degli insiemi si dimostra che un errore di controllo sufficientemente ampio può essere diretto verso l’origine e tenuto in un dintorno dell’origine ben definito. MPC richiede che in ogni istante di campionamento si risolva un problema di ottimizzazione (constrained finite time optimal control, CFTOC). La limitata potenza di calcolo dei microcontrollori e la brevità dei periodi di campionamento richiedono un CFTOC relativamente semplice, che si può ottenere utilizzando un modello di flusso virtuale nel sistema statico di riferimento. Scegliendo piccoli orizzonti di predizione si limita la dimensione del CFTOC, la cui risoluzione necessità di algoritmi efficienti, che permettano di ottenere un risultato all’interno di un periodo di campionamento. Il CFTOC di CCS-MPC è un programma (convesso) lineare o quadratico (linear program, lp; quadratic program, qp) che può essere risolto tramite algoritmi efficienti e noti. Al fine di elaborare una strategia di tipo minimalista, viene introdotto un algoritmo efficiente che risolve analiticamente il problema con un orizzonte di predizione di un passo. Il CFTOC di FCS-MPC è un problema di programmazione lineare o quadratico a numeri misti interi (mixed-integer) ed è quindi più difficile da risolvere con metodi numerici standard. In pratica si calcolano tutte le soluzioni possibili, tra le quali viene scelta la soluzione ottimale. Per migliorare l’efficienza di calcolo si combina quest’approccio con tecniche branch-and-bound e branch-and-cut. Gli algoritmi di controllo sono stati sviluppati su una piattaforma software-in-the-loop (SiL) basata su Matlab/Simulink e il codice di programmazione è stato implementato su un banco di prova sperimentale, senza modifiche. La valutazione approva la progettazione e la realizzazione di CCS-MPC e FCS-MPC e indica buoni risultati sia nell’operazione dinamica che in quella stazionaria. I due approcci MPC hanno proprietà diverse che risultano vantaggiose per applicazioni differenti. CCS-MPC ha una frequenza di commutazione costante ed è un’alternativa promettente al controllo vettoriale proporzionale-integrale (PI). Il concetto può essere combinato con diversi schemi di modulazione, nella fattispecie si usa la modulazione simmetrica di vettori spaziali (symmetric space vector modulation, SSVM) e la modulazione discontinua di vettori spaziali (discontinuous space vector modulation, DSVM). FCS-MPC tiene conto della commutazione dell’inverter e raggiunge all’incirca un ripple di commutazione costante, ma ottiene una frequenza di commutazione variabile. Il concetto è vantaggioso per sistemi dove è richiesta un frequenza di campionamento alta rispetto alla frequenza di commutazione, per esempio azionamenti ad alta potenza o servoazionamenti. Inoltre, lo spettro della corrente di FCS-MPC non contiene armoniche PWM e di conseguenza è vantaggioso in termini di rumore acustico, data la mancanza di toni distinti. Tuttavia, le armoniche PWM distinte di CCS-MPC sono più semplici da filtrare. Si può concludere affermando che lo studio del problema dei controlli avanzati di coppia per azionamenti con un motore sincrono a magneti permanenti, ha portato all’individuazione di una strategia innovativa. L’introduzione di una nuova struttura di controllo ha semplificato notevolmente il problema di controllo predittivo, con particolare attenzione al concetto di stabilità. Inoltre, le implementazioni di tale struttura si sono rivelate particolarmente efficaci su piano computazionale.

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Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq
This work presents study of nonlinear predictive controller, tuned by optimization process, applied to independent excitation DC motor speed control, controlled by fully controlled three phase rectifier. The methodology starts from the construction of the workbench that represents the real system followed by the development and validation of the computational model. The optimization process promotes the obtaining of optimized parameters for the nonlinear model based predictive controller to be implemented in the real process. Comparisons are made between the control technique proposed with classical control techniques, in computational and real environment. The results indicate the prominence of the proposed technique to be used in control of non-linear systems where seeks smaller errors even with disturbance insertions.
Este trabalho apresenta estudo de controlador preditivo não linear, sintonizado por processo de otimização, aplicado ao controle de velocidade de motor de corrente contínua de excitação independente acionado por retificador trifásico totalmente controlado. A metodologia parte da construção da bancada que representa o sistema real seguida pelo desenvolvimento e validação de modelo computacional. O processo de otimização, promove a obtenção de parâmetros otimizados para o controlador preditivo não linear baseado em modelos a serem implementados no processo real. São realizadas comparações entre a técnica de controle proposta com técnicas de controle clássicas, em ambiente computacional e real. Os resultados indicam a proeminência da técnica proposta a ser empregada em controle de sistemas não lineares onde busca-se menores erros mesmo com inserção de distúrbios.

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This work presents a comparison between Fuzzy and dynamic matrix controllers. These controllers are applied to the direct current (DC) motor speed control, triggered by fully controlled three-phase rectifier. The construction of the real system and the development and validation of the computational model are described. The controllers’ parameters are obtained through an optimization process. Both control techniques are compared and results indicate better performance of the optimized controllers, which suggest their promise in nonlinear systems’ control, in which seeks out control without error, that fulfills well its duty and its able to resist the fatigues.
Este trabalho apresenta o comparativo entre os controladores Fuzzy e matriz dinâmica. Estes controladores são aplicados ao controle de velocidade do motor de corrente contínua, acionado por retificador trifásico totalmente controlado. A metodologia parte da construção do sistema real e do desenvolvimento e validação do modelo computacional. A obtenção dos parâmetros dos controladores é realizada através do processo de otimização. Realiza-se análise comparativa entre as técnicas de controle e os resultados apontam para a proeminência de controladores sintonizados via processo de otimização como técnica promissora a ser empregada em controle de sistemas não lineares, nos quais buscam-se controle em que não há erro, que cumpra bem o seu dever e apto para resistir às fadigas.

Orientador: Edson Bim
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Resumo: Esta tese trata do emprego do controle preditivo baseado no modelo (MBPC-Model Based Predictive Control) no acionamento do motor de indução do trifásico, para controle de fluxo de rotor e velocidade. A estratégia MBPC baseia-se na minimização do erro entre as referências futuras e a predição do modelo, para gerar os sinais de controle. Nesta tese, o motor de indução é descrito por espaço de estados e, diferentemente, do MBPC não linear, que emprega algoritmos de busca para determinar os sinais de controle, a estratégia escolhida faz inearizações sucessivas. Assim sendo, a cada ciclo gera-se a lei de controle, sendo que esta é dada por uma equação algébrica. São necessários ao controlador preditivo o conhecimento das tensões de terminal do estator e das seguintes variáveis de estado: corrente de estator, fluxo de rotor e velocidade de eixo. Para a estimação dos estados é empregado o filtro de Kalman estendido. O torque de carga é tratato como uma perturbação e sua magnitude é obtida por duas abordagens: pela equação eletromecânica e pelo filtro de Kalman estendido. Resultados de simulação computacional e experimentais validam a proposta
Abstract: This thesis presents the results concerning the control of rotor flux and speed of the induction motor using MBPC strategy, which is based on the error minimization between the future set point and model prediction, resulting in control signals. In the case studied in this thesis the motor model is described in space-state. The non linear MBPC emploies search algorithms to find the control signals, whereas the technique used in this thesis made sucessives linearizations on model; therefore in every control cicle a new algebraic control lay is found. The predictive control needs to know the stator voltage and the following state variables: stator current, rotor flux and speed. In the order to estimate the states an extended Kalman filter is employed. The load torque is considered as a disturbance and its amplitude is obtained in two ways: by calculation via eletromechanical equation and by estimation via Kalman filter. The proposal has been validated by imulations and experiments
Doutorado
Energia Eletrica
Doutor em Engenharia Elétrica

Alcune aree definite dall'Unione Europea nel contesto delle smart cities and communities si fondono pienamente con i motori elettrici come, per esempio, l'efficienza energetica, le tecnologie a basse emissioni di carbonio e la mobilità. I motori elettrici sono utilizzati in molteplici applicazioni industriali e non, consumando tra il 43% e il 46% dell'energia elettrica prodotta su scala mondiale.Nonostante alcune applicazioni siano contraddistinte da dinamiche elevate, come manipolatori o macchine utensili, la maggior parte di esse sono caratterizzate da basse dinamiche in quanto facenti parte di processi industriali, per esempio pompe, compressori, ventilatori o nastri trasportatori. Si è stimato che il costo dell'intero ciclo di vita di un motore elettrico è ascrivibile per il 92% - 95% all'energia consumata, il che indurrebbe un tempo di ritorno dall'investimento per installazione di un azionamento elettrico minore di due anni. Nonostante il notevole risparmio economico e ambientale ottenibile, è piuttosto sorprendente apprendere che solo il 10% - 15% di tutti i motori industriali siano controllati da azionamenti elettrici. Per quanto riguarda le diverse tecnologie di motori elettrici, i motori sincroni a riluttanza stanno ricevendo una notevole attenzione sia da ricercatori industriali che accademici. Il crescente interesse è principalmente motivato dalle loro intrinseche caratteristiche quali l'alta efficienza, il basso costo e il basso impatto ambientale dovuto alla mancanza di magneti permanenti. Per di più, le loro caratteristiche soddisfano appieno i requisiti imposti dalle smart cities and communities e sono adatti per tutte le applicazione, caratterizzate da una bassa dinamica, viste sopra. Per questi motivi, questa tecnologia di motori può essere posta al centro dei processi di rinnovamento di quelle applicazioni. Vi è ampio consenso sul potenziale incremento delle vendite sia di azionamenti elettrici che di motori sincroni a riluttanza. I motori sincroni a riluttanza sono soggetti a una marcata saturazione magnetica, rendendo i classici modelli a parametri concentrati poco adatti. La prima parte di questa tesi riguarda lo sviluppo di un innovativo modello magnetico per motori anisotropi. Si basa su una rete neurale non tradizionale, chiamata Radial Basis Function. La sua proprietà locale rende questo tipo di rete neurale particolarmente adatta ad un addestramento durante il normale funzionamento del motore. Si propone una completa procedura di design e addestramento della stessa. In particolare vengono fatte alcune considerazione le quali permettono di definire a priori alcuni parametri della rete neurale rendendo il problema di addestramento lineare. Si descrivono due algoritmi di addestramento, il primo veloce ma computazionalmente dispendioso perciò adatto per un'implementazione offline mentre il secondo idoneo ad un addestramento online. Infine, per concludere l'identificazione parametrica del motore, si propone uno schema basato sull'iniezione di una corrente continua il quale permette di stimare la resistenza di statore indipendentemente da tutti gli altri parametri della macchina. L'indipendenza parametrica permette un notevolmente miglioramento nell'accuratezza di stima del modello magnetico ottenuto con la rete neurale. La seconda parte di questa tesi, invece, tratta il controllo del motore e come sia possibile migliorarne le performance utilizzando il modello identificato. Innanzitutto, per incrementarne l'efficienza si presenta un innovativo metodo per trovare la curva a massima coppia per corrente. La tecnica proposta lavora in stretta simbiosi con l'identificazione del modello magnetico in quanto è in grado di capire dove si trova la curva cercata rispetto all'attuale punto di lavoro sfruttando la stima locale dei flussi magnetici. Identificata la direzione di movimento, l'azionamento continuamente muove il punto di lavoro coerentemente. Infine, si propongono tre diversi controlli di corrente pensati per gestire un motore fortemente non lineare, tutti basati sul modello stimato. Il primo è un controllore proporzionale-integrale nel quale i parametri vengono modificati al variare del punto di lavoro con lo scopo di mantenere la dinamica della corrente di motore costante. Il secondo è anch'esso basato su un controllore proporzionale-integrale ma a guadagni costanti accoppiato ad un'azione di feed--forward la quale compensa tutte le non linearità presenti nella mappa magnetica. Infine, il terzo è un controllo predittivo il quale determina direttamente la posizione degli switch tali per cui la funzione di costo è minimizzata. All'interno del controllo, è inserito un vincolo sulla corrente massima e si utilizza un particolare algoritmo per ottenere un lungo orizzonte di predizione. Tutti i metodi presentati nella tesi sono stata verificati attraverso dettagliate simulazioni e prove sperimentali, eccezione fatta per il controllo predittivo il quale è stato testato attraverso simulazioni.
Smart cities and communities are conjugated by European Union in different areas, including energy efficiency, low carbon technologies and mobility which are deeply merged with electric motors. Electric machines are ubiquitous in industry for a wide range of applications, consuming between 43% and 46% of all electricity that is generated in the world. Although some machines are used for high-performance applications, such as robots and machine tools, the majority are used in industrial processes for pumps, compressors, fans, conveyors, and other slower-dynamic applications. It is estimated that 92% - 95% of the life cycle costs of electric motors are associated with the energy they consume, leading to typical payback periods of < 2 years for the installation of an adjustable-speed drive. It is rather surprising to learn that, despite overwhelming evidence of the attainable savings, only 10% - 15% of all industrial motors presently use electronic adjustable speed drives. On the motor side, Synchronous Reluctance (SynR) motors are gaining lots of attention from industrial researchers and academics, due to their inherent characteristics like the high efficiency, the low cost and the low environmental footprint. Their characteristics fully meet the requirements imposed by smart cities and communities and the aforementioned low-dynamics applications, so they could be the heart of the revamping of those plants. There is wide agreement that the potential for future growth in the sales of industrial drives and SynR motors is still very substantial. SynR motors are prone to magnetic saturation, making the classic model with lumped parameters unsuitable. The main part of this thesis concerns the development of a new magnetic model for anisotropic motors, especially for SynR motors. It is based on a special kind of neural network (NN), called Radial Bases Function (RBF) NN, which is particularly advisable for an online updating due to its local property. A complete training procedure is proposed in which some considerations are done to define several NN parameters and to convert the nonlinear training problem into a linear one. Two different training algorithms are presented, the former one is fast but computationally cumbersome then suitable for an offline training while the latter one is lighter then proper for an online training. In order to complete the online parameters identification, a scheme based on a DC current injection is developed to estimate the stator resistance. An exhaustive analysis is carried out to disclose that the proposed method is independent from other motor parameters which is a strength asset in a saturable motor. An accurate stator resistance value improves in turn of the magnetic model. The second part of this dissertation deals with how to exploit an accurate magnetic model to enhance the motor control. In order to improve the efficiency of the motor, exploiting the RBF NN model and the online training algorithm, the Maximum Torque per Ampere (MTPA) curve is found. Starting from a blank NN, it is continuously online trained and a proper algorithm understands where the MTPA curve is respect to the current working point. Afterwards, the drive moves itself towards the actual MTPA. Finally, three different current control schemes tailored for anisotropic motors are presented, all based on the available NN-based magnetic model. The first one is a gain-scheduling PI control where the control gains are accordingly tuned to the working point to keep constant the control bandwidth. The second one is based on a classical PI regulator with a FF action to compensate for all the nonlinearity of magnetic maps. The third one is a constrained direct Model Predictive Control (MPC) where a long prediction horizon is achieved. In order to accomplish a long prediction horizon, the Sphere Decoding Algorithm is properly modified to make it suitable for a nonlinear system. The whole thesis was fully validated through an intensive simulation and experimental stage, except the long--horizon MPC which was tested only by simulation.

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior
O Motor de RelutÃncia VariÃvel (MRV) vem cada vez mais chamando a atenÃÃo da indÃstria e da comunidade acadÃmica. Isso se deve ao crescente desenvolvimento da eletrÃnica de potÃncia e na Ãrea de microprocessadores nos Ãltimos anos, o que permitiu o avanÃo de outros sistemas de acionamentos tais como com MRV. A competitividade do MRV se justifica por seu baixo custo de produÃÃo e manutenÃÃo, uma elevada densidade de potÃncia, robustez e resistÃncia a faltas. O presente trabalho propÃe um esquema de controle robusto baseado em um Controlador Preditivo Generalizado (GPC) pertencente a famÃlia de Controladores Preditivos Baseados em Modelo (MPC) aplicados a malha de corrente e velocidade de um sistema de acionamento com MRV. O controlador proposto, assim como controladores tradicionais aplicados neste tipo de sistema tais como o controlador por Histerese e o controlador PID sÃo tambÃm aplicados com o objetivo de proporcionar meios de comparaÃÃo dos resultados experimentais obtidos. A estrutura do controlador à baseada no projeto de um filtro de modo a permitir uma resposta rÃpida, rejeiÃÃo a distÃrbios, atenuaÃÃo de ruÃdos e robustez com um baixo custo computacional. O controlador proposto foi implementado e os resultados comparados com controladores tradicionais e analisados quantitativamente por meio de Ãndices de desempenho. Para execuÃÃo das rotinas de controle foi utilizado um DSP das Texas Instruments (TMS320F28335), sendo suas caracterÃsticas principais apontadas. O algoritmo do software de controle à esquematizado. O trabalho fez uso da bancada de pesquisa em MRV do laboratÃrio do Grupo de Pesquisa em AutomaÃÃo e RobÃtica (GPAR) da Universidade Federal do Cearà (UFC).

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Model-based predictive control (MPC) approaches has been studied in a wide range of areas, as petrochemical and aerospace, mainly due to its capability of easily deal with physical and operational constraints. Moreover, such approaches can be extended for the application in control loops with nonlinear and time-variant systems. At this context, the objective of this work is to study some MPC techniques in order to evaluate their applicability to control a three-phase induction motor. More specifically, it was analyzed a Dynamic Matrix Control (DMC) approach, as well as two MPC techniques that uses state space modeling. The control algorithms in question and the nonlinear mathematical model of the motor in study were programmed using the free computing environment Scilab-Xcos®. The models of the threephase motor used in the MPC were obtained by a system identification method (based on the step response of the classical non-linear motor model) and by a phenomenological three-phase modeling approach. Multiple simulations have been performed considering variations in load and speed reference. Besides, some discussions are made related to the influence of the control parameters and about the computational cost. Finally, the results showed that the use of MPC techniques in induction machines has great potential.
Abordagens de controle preditivo baseado em modelo (MPC, do inglês model-based predictive control) têm sido estudadas em diversas áreas, como petroquímica e aeroespacial, principalmente devido à capacidade que apresentam em tratar restrições físicas e operacionais de forma simples. Além disso, tais abordagens podem ser estendidas para aplicação em malhas de controle de sistema não lineares e variantes no tempo. Nesse contexto o objetivo desse trabalho é estudar algumas técnicas de MPC a fim de avaliar sua aplicabilidade no controle de um motor de indução trifásico. Mais especificamente, é analisada a técnica DMC (do inglês Dynamic Matrix Control) bem como duas técnicas de MPC que utilizam modelos no espaço de estados. Os algoritmos de controle em questão e o modelo matemático não linear do motor estudado foram programados utilizando o Scilab-Xcos®, um ambiente de processamento de código livre. Os modelos do motor de indução trifásico utilizados no MPC foram obtidos por meio de um método de identificação de sistemas (baseado na resposta ao degrau do modelo clássico não linear do motor) e por uma abordagem de modelagem fenomenológica trifásica. Múltiplas simulações foram realizadas, considerando variações de carga e referência de velocidade, sendo então apresentadas algumas discussões sobre a influência dos parâmetros de controle e custo computacional. Finalmente, os resultados obtidos demonstraram que a aplicação de técnicas MPC em máquinas de indução apresenta um grande potencial.

Neste trabalho investiga-se a aplicação de um algoritmo genético multiobjetivo, ferramenta que se destaca por sua flexibilidade e interpretabilidade, na obtenção de fatores de ponderação para aplicação no controle preditivo de torque do motor de indução, ou Model Predictive Torque Control (MPTC). O MPTC busca minimizar a cada instante de atuação uma função custo que representa o sistema, destacando-se pela rápida resposta de torque, facilidade de incorporar restrições e ausência de modulador de tensão. No entanto, essa técnica apresenta fatores de ponderação em sua estrutura de cálculo que não dispõem de métodos analíticos de projeto. Utilizou-se o algoritmo genético de classificação nãodominada, ou Non-dominated Sorting Genectic Algorithm II (NSGA-II), projetado de forma a obter soluções que busquem o compromisso entre o desempenho dinâmico do motor, via minimização das oscilações de torque e fluxo, e a eficiência energética do sistema por meio da minimização da frequência média de chaveamento da eletrônica de potência. Resultados simulados e experimentais mostraram que o conjunto de soluções fornecido pelo NSGA-II é factível e contrapõe as oscilações de torque e de fluxo e a frequência média de chaveamento, cabendo à aplicação desejada a escolha da solução. Com isso, tem-se uma ferramenta de projeto dos fatores de peso do MPTC capaz de incorporar restrições e ajustar vários fatores ao mesmo tempo.
This work investigates the application of a multi-objective genetic algorithm to obtain a set of weighting factors suitable for use in Model Predictive Torque Control (MPTC) of a induction motor variable speed drive. MPTC approach aims at minimizing a cost function at each step, and is highlighted for its fast torque response, facility to incorporate system constraints and the absence of voltage modulators. Nevertheless, MPTC structure presents weighting factors in the cost function which lack of an analytical design procedure. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was designed for a trade-off between torque and flux ripples minimization and minimization of the average switching frequency of the system. Simulated and experimental results showed NSGA-II offered a Pareto set of feasible solutions, so that torque ripple, flux ripple or average switching frequency can be minimized, depending on the solution chosen according to project demand. Thereby, there is a project tool for MPTC weighting factors able to adjust several factor at the same time, incorporating desired restrictions.

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This work presents an implementation and analysis of traction control and linear trepidation techniques, driven by a six - pulse fully controlled three - phase rectifier. The methodology addresses the construction of real reality, modeling by method of system identification, design and tuning of optimization processes. The comparisons between the techniques are their characteristics and their performances when performing statistics, verifying the robustness of the series in non-linear systems. Both techniques perform satisfactory in the execution of the control, correlating with the.
Este trabalho apresenta a implementação e análise das técnicas de controle por modos deslizantes e preditivo não linear, aplicados no controle de velocidade de motor de corrente contínua de excitação independente, acionado por retificador trifásico totalmente controlado de seis pulsos. A metodologia aborda a construção da bancada real, modelagem por método de identificação de sistemas, projeto e sintonia dos controladores utilizando processo de otimização. São realizadas comparações entre as referidas técnicas destacando suas características e desempenhos quando executadas em condições semelhantes, verificando a robustez das mesmas atuando em sistemas não lineares. Ambas as técnicas apresentam desempenho satisfatório na execução do controle, dependendo portanto, da análise do sistema a ser implementado para a determinação do método apropriado.

This work deals with the predictive control algorithms of the AC drives. The introductory section contains summary of current state of theory and further description and classification of most significant predictive algorithms. A separate chapter is dedicated to linear model predictive control (linear MPC). The main contribution of this work is the introduction of two new predictive control algorithm for PMSM motor, both of which are based on linear MPC. The first of these algorithms has been created with the aim of minimizing its computational demands, while the second algorithm introduces the ability of field weakening. Both new algorithms and linear MPC were simulated in MATLAB-Simulink.

The research presented in this thesis involves different aspects related to advanced control methodologies and self-commissioning identification algorithms in modern electrical drives. The theoretical study and the validation of the results obtained were performed in the three years of Ph.D. at the Electric Drives Laboratory in the Department of Management and Engineering of the University of Padova, (VI) Italy. The research topics were mainly three, all related to the implementation and development of advanced controls for electric drives, aimed at a more efficient use of the electric machines in the modern mechatronic applications. The demand of electric drives capable of guarantee high-performance and flexible enough to update in real time the parameters involved in the control algorithm are the motivation of the present research, as well as the meshing or replacement of standard or obsolete control techniques with modern ones, able to fully exploit the new hardware resources. In order to contextualizes and motivate the choice of the present research in the world scenario, a comprehensive bibliographic framework can be found in the introduction of each chapter of the thesis. The part one of the thesis presents two new control architectures for Permanent Magnet Synchronous Motors, that is a type of electric machine notoriously appreciated by both academia and industry for its flexibility of use and controllability. To this aim, in Chap.2 is proposed a non-linear control algorithm for the automatic search of the Maximum Torque Per Ampere (MTPA) operating condition for Permanent Magnet Synchronous Motors with anisotropic structure, to be integrated in a conventional Field Oriented Control scheme. The exhaustive convergence and stability analysis performed in order to derive a new and original tuning method of the controller (proven by numerous experimental evidences) is definitely one of the distinguishing features in this research topic. In parallel to the first topic, for the same type of motor has been investigated and developed (first analytically and then by simulation) a speed and current Direct Predictive Control with Hierarchical decisional structure. Unlike the traditional control techniques, the proposed Direct Predictive Control with modified hierarchical control structure has a faster dynamic and the capability to impose different operating conditions aimed at the energy efficiency optimisation. The on-line execution of the algorithm required for the experimental validation, has become possible thanks to the adoption of a control platform based on FPGA logic (Chap.3). In fact, the processing speed provided by these devices, released from the execution of sequential instructions (typical of the architecture of the microprocessors), ensures an execution time of the algorithm contained in a few us. The part two of the thesis (i. e. Chap.5) presents an innovative technique of parameter identification for induction motors, capable of estimating the parameters of the equivalent inverse-Gamma electric circuit completely at standstill. As known, the saturations in the parameters of the magnetic circuit of the induction motor and the relative nonlinearities, deteriorate the performance of the standard sensored or sensorless vectorial controls. The studied self-commissioning procedure addresses and solves many problems related to the estimate of the non-linearity of the parameters, and then it can be considered as an evolution of the classical identification techniques in the literature. The practical feasibility, doubly validated by numerous experimental tests and by many finite element simulations on three different induction motors, concludes the chapter and proves definitely the method.
La ricerca presentata in questa tesi coinvolge molteplici aspetti che si legano alle più recenti metodologie di controllo studiate per azionamenti elettrici di ultima generazione. Lo studio teorico e la validazione in ambito sperimentale sono il frutto del lavoro svolto nel triennio di dottorato presso il laboratorio di azionamenti elettrici del Dipartimento di Tecnica e Gestione dei Sistemi Industriali dell’Università degli Studi di Padova. I temi di ricerca trattati sono principalmente tre, tutti legati alla realizzazione e allo sviluppo di algoritmi di controllo innovativi, capaci di incrementare l’efficienza e le prestazioni delle macchine elettriche di ultima generazione per applicazioni meccatroniche. Azionamenti elettrici in grado di garantire elevate prestazioni ma sufficientemente flessibili da aggiornare in tempo reale i diversi parametri coinvolti nel algoritmo di controllo sono il filo conduttore e la motivazione della presente ricerca, così come la sostituzione di logiche di controllo standard o obsolete con nuove architetture di controllo capaci di sfruttare le più recenti innovazioni hardware. Al fine di contestualizzare e motivare la ricerca condotta nel panorama mondiale, nell’introduzione di ciascun capitolo è inserito un esaustivo inquadramento bibliograficoinerente inerente il problema affrontato. La prima parte della tesi presenta due nuove architetture di controllo per motori sincroni a magnete permanente, tipologia di macchina elettrica notoriamente apprezzata dal mondo accademico e industriale sia per la sua flessibilità d’uso che per la sua facile controllabilità. In tal senso, nel Capitolo2 è descritto e formalizzato un controllo non lineare per motori sincroni a magnete permanente anisotropi, inseribile in schemi di controllo convenzionali ad orientamento di campo per ottenere la condizione di funzionamento a massima coppia su corrente (MTPA). L’esaustiva analisi di convergenza e stabilità condotta al fine di ottenere un nuovo ed originale metodo per la sintonizzazione del regolatore (comprovato da numerose evidenze sperimentali) è sicuramente una delle caratteristiche distintive per questo ramo della ricerca. Per la stessa tipologia di motore è stato poi sviluppato un controllo predittivo a stati finiti con struttura decisionale gerarchica. A differenza delle tecniche di controllo tradizionali, la soluzione studiata garantisce una dinamica veloce e la possibilità di imporre condizioni operative diverse, volte all’ottimizzazione e all’incremento dell’efficienza energetica. L’esecuzione on-line di tale algoritmo per le verifiche sperimentali si è resa fattibile grazie all’adozione di una piattaforma di controllo basata su logica FPGA (Capitolo3), in quanto la velocità di calcolo offerta da tali dispositivi, svincolata dall’esecuzione sequenziale delle istruzioni tipica dei microprocessori, garantisce tempi di esecuzione dell’algoritmo contenuti a pochi us. Nella seconda parte della tesi (Capitolo5) è presentata un innovativa tecnica di identificazione parametrica per motori asincroni, capace di stimare i parametri del circuito equivalente a Gamma-inverso del motore asincrono, a rotore fermo. Come noto, le saturazioni del circuito magnetico della macchina e le non linearità ad esso associate deteriorano le performances nei normali controlli vettoriali sensored e soprattutto sensorless. Il metodo di identificazione parametrica studiato affronta e risolve molti problemi connessi alla stima delle non linearità dei parametri, configurandosi a tutti gli effetti come un evoluzione delle classiche tecniche di identificazione presenti in letteratura. La fattibilità pratica del metodo, validata con innumerevoli prove sperimentali e simulazioni agli elementi finiti su tre diversi motori ad induzione, conclude il capitolo e prova in modo definitivo la realizzabilità del metodo.

Speed-accuracy tradeoffs, velocity profiles, and physiological tremor are fundamental characteristics of human movement. The principles underlying these phenomena have long attracted major interest and controversy. Each is well established experimentally but as yet they have no common theoretical basis. It is proposed that these three phenomena occur as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of adaptive model theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (i) analysing sensory information, (ii) planning a desired optimal response, and (iii) executing that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory of variable duration, or horizon, to connect the actual response with the predicted future state of the target and compensate for executional error. BUMP model simulation studies show that intermittent adaptive optimal control employing two extremes of variable horizon predictive control reproduces almost exactly findings from several authoritative human experiments. On the one extreme, simulating spatially-constrained movements, a receding horizon strategy results in a logarithmic speed-accuracy tradeoff and accompanying asymmetrical velocity profiles. On the other extreme, simulating temporally-constrained movements, a fixed horizon strategy results in a linear speed-accuracy tradeoff and accompanying symmetrical velocity profiles. Furthermore, simulating ramp movements, a receding horizon strategy closely reproduces experimental observations of 10 Hz physiological tremor. A 100 ms planning interval yields waveforms and power spectra equivalent to those of joint-angle, angular velocity and electromyogram signals recorded for several speeds, directions, and skill levels of finger movement. While other models of response planning account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.

Augmentar l’ús d’energia provinent de fonts renovables és important en la lluita contra el canvi climàtic. No obstant, la seva implantació planteja reptes importants deguts a la manca de continuïtat en la seva generació i al desajust que existeix amb els perfils de consum. La present tesi doctoral s’emmarca en dues propostes per incrementar el rendiment dels panells fotovoltaics en l’àmbit dels sistemes de calefacció per edificis. Per una banda, el sistema integra un tanc d'emmagatzematge d'energia tèrmica, que permet emmagatzemar l'energia generada pels panells durant el dia, a fi de poder-la consumir a les hores amb més demanda. D'altra banda, el sistema també compta amb una estratègia de control predictiu, que permet pronosticar les condicions meteorològiques i les demandes de calefacció futures, per tal d'ajustar el funcionament de tot el conjunt d'elements, considerant aquesta informació. El sistema proposat ha demostrat ser efectiu en diferents tipus de clima i habitatges.
Aumentar el uso de energía procedente de fuentes renovables es importante en la lucha contra el cambio climático. No obstante, su implantación plantea retos importantes debidos a la falta de continuidad en su generación y al desajuste que existe con los perfiles de consumo. La presente tesis doctoral se enmarca en dos propuestas para incrementar el rendimiento de los paneles fotovoltaicos en el ámbito de los sistemas de calefacción para edificios. Por un lado, el sistema integra un tanque de almacenaje de energía térmica, que permite almacenar la energía generada por los paneles durante el día, a fin de poderla consumir a las horas con más demanda. Por otro lado, el sistema también cuenta con una estrategia de control predictivo, que permite pronosticar las condiciones meteorológicas y las demandas de calefacción futuras, para ajustar el funcionamiento de todo el conjunto de elementos, considerando esta información. El sistema propuesto demostró ser efectivo en distintos tipos de climas y viviendas.
To increase the use of energy that comes from renewables is important to fight against climate change. However, their deployment leads to significant challenges due to the intermittence in their generation and the mismatch between energy demand and supply. In that sense, this PhD thesis is framed in two proposals to increase the performance of photovoltaic panels in heating systems integrated in the building sector. On the one hand, the system considers a thermal energy storage tank, which allows to store the energy produced by the panels during the solar hours, in order to consume it along the peak demand periods. On the other hand, the system also takes into account a model predictive control strategy, which enables to forecast weather conditions and future heating demands, to adjust the operation of all the elements. The proposed system demonstrated a good and effective behaviour in different climate conditions and buildings.

Starting a few decades ago, the unmanned wheeled vehicle research has drawn lately more attention, especially for off-road environment. As the demand to use electric vehicles increased, the need to conceptualize the use of electrically driven vehicles in autonomous operations became a target. That is because in addition to the fact that they are more environmentally friendly, they are also easier to control. This also gives another reason to enhance further the energy economy of those unmanned electric vehicles. Off-road vehicles research was always challenging, but in the present work the nature of the off-road land is utilized to benefit from in order to enhance the energy consumption of those vehicles. An algorithm for energy consumption optimization for electrically driven unmanned wheeled vehicles is presented. The algorithm idea is based on the fact that in off-road conditions, when the vehicle passes a ditch or a hole, the kinetic energy gained while moving downhill could be utilized to reduce the energy consumption for moving uphill if the dimensions of the ditch/hole were known a distance ahead. Two manipulated variables are evaluated: the wheels DC motors supply voltage and the DC armature current. The developed algorithm is analysed and compared to the PID speed iii controller and to the open-loop control of DC motors. The developed predictive controller achieved encouraging results compared to the PID speed control and also compared to the open-loop control. Also, the use of the DC armature current as a manipulated variable showed more noticeable improvement over using the DC input voltage. Experimental work was carried out to validate the predictive control algorithm. A mobile robot with two DC motor driven wheels was deployed to overcome a ditch-like hindrance. The experimental results verified the simulation results. A parametric study for the predictive control is conducted. The effect of changing the downhill angle and the uphill angle as well as the size of the prediction horizon on the consumed electric energy by the DC motors is addressed. The simulation results showed that, when using the proposed approach, the larger the prediction horizon, the lower the energy consumption is.

This thesis describes the theory of model predictive control and application of the theory to synchronous drives. It shows explicit and on-line solutions and compares the results with classical vector control structure.

Orientador: Ernesto Ruppert Filho
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Resumo: A energia eólica surge como alternativa à crescente demanda por energia elétrica e as preocupações com as reduções de emissão de materiais poluentes no mundo todo. Nesse contexto, o objetivo desta tese é o de propor o uso de três tipos de controladores de potências ativa e reativa do gerador de indução trifásico com rotor bobinado para uso em parques eólicos. Os controladores propostos são o controlador deadbeat, o controlador por desacoplamento de fluxo de enrolamento de estator associado com o controlador deadbeat e, finalmente, o controlador preditivo, todos eles baseados na modelagem dinâmica do gerador. O gerador tem tanto seu enrolamento de estator diretamente conectado à rede elétrica e seu enrolamento de rotor conectado à rede através de um conversor bidirecional que permite ao fluxo de potência apresentar um comportamento bidirecional. Avalia-se também o desempenho dos controladores de potências mencionados quando existem erros nos parâmetros estimados do gerador. Resultados de simulação computacional do modelo matemático dinâmico do sistema bem como resultados experimentais obtidos em uma montagem de bancada são apresentados para comprovação das propostas.
Abstract: Wind energy is an alternative to the growing demand for electricity and concerns about emission reductions of pollutants worldwide. In this context, the objective of this thesis is to propose the use of three types of real and reactive power controllers of the wound rotor three phase induction generator to be used in wind farms. The proposed controllers are the deadbeat controller, the controller by decoupling stator winding magnetic flux associated with the deadbeat controller and finally, the predictive control, all based on the generator dynamic mathematical model. The generator has its stator windings directly connected to the grid as its rotor windings connected to the network through a bi-directional converter that allows the power flow in the two directions. It also evaluates the performance of the mentioned power controllers when there are errors in the estimated generator's parameters. Results of computer simulations of the system dynamic mathematical model and experimental results obtained on a laboratory assembly are presented to check the proposals.
Doutorado
Energia Eletrica
Doutor em Engenharia Elétrica

This thesis contains original research into the propagation of sound in acoustically lined ducts with flow. The motivation for this work is the requirement to predict the sound attenuation of acoustic liners in the bypass duct of modern turbofan aeroengines. The liners provide the most effective means with which to suppress the rear fan noise. It is therefore important to make the best possible use of the available lined area by optimising the liner configuration. A set of analytic and numerical methods for predicting the liner attenuation performance have been developed, which are suitable for use in intensive liner optimisation studies, or as preliminary design tools. Eigenvalue solvers have been developed to find modal solutions in rectangular ducts with uniform flow and annular ducts with sheared flow. The solvers are validated by replicating results from the scientific literature and the Finite Element method. The effect of mean core flow radial profile and boundary layers on the mode eigenfunctions and axial decay rates are considered. It is shown that solutions for thin boundary layer flows converge to those based on the commonly used slip flow boundary condition. It is demonstrated that realistic flow profiles should be used to assess acoustic mode propagation in bypass ducts. The flow profile can have strong effects upon low order modes and surface waves, and in fact at high frequencies, the profile can affect all the modes. Mode-matching schemes are developed to assess the power attenuation performance and modal scattering of finite length liners. The results of the schemes are used to show that refraction of sound by boundary layers increases attenuation at high frequency. Power attenuation is higher where the mean core flow gradient refracts sound towards the liner. It is found that asymmetric liners can provide improved attenuation, depending on the direction of the mean flow shear gradient. The optimisation of axially-segmented liners for single and multi-mode sources is demonstrated. It is found that potentially large improvements in the attenuation of tonal noise is possible, whilst benefits for broadband noise are more difficult to achieve.

The aim of this Master's Thesis was to develop a naturally controllable BCI that can predict motion trajectories from the imagination of motor execution. The approach to reach this aim was to nd a correlation between movement and brain data, which can subsequently be used for the prediction of movement trajectories only by brain signals. To nd this correlation, an experiment was carried out, in which a participant had to do triggered movements with its right arm to four di erent targets. During the execution of the movements, the kinematic and EEG data of the participant were recorded. After a preprocessing stage, the velocity of the kinematic data in x and y directions, and the band power of the EEG data in di erent frequency ranges were calculated and used as features for the calculation of the correlation by a multiple linear regression. When applying the resulting regression parameter to predict trajectories from EEG signals, the best accuracies were shown in the mu and low beta frequency range, as expected. However, the accuracies were not as high as necessary for control of an application.
El objetivo de esta Tesis de Maestría fue desarrollar un interfaz cerebro computador controlable naturalmente que pueda predecir trayectorias de movimiento imaginadas. El enfoque para alcanzar este objetivo fue encontrar una correlación entre el movimiento y los datos cerebrales que puedan ser utilizados posteriormente para la predicción de las trayectorias de movimiento sólo por medio de señales cerebrales. Para encontrar esta correlación, se realizó un experimento, en cual un participante tuvo que realizar movimientos desencadenados con su brazo derecho a cuatro puntos diferentes. Durante el examen de los movimientos, se registraron los datos cinemáticos y de EEG del participante. Después de una etapa de pre-procesamiento, se calcularon las velocidades en las direcciones x y y, de los datos cinemáticos, y la potencia de la banda, de los datos EEG en diferentes rangos de frecuencia, y se utilizaron como características para el cálculo de la correlación mediante con una regresión lineal múltiple. Al aplicar el parámetro de regresión resultante para predecir trayectorias a partir de señales de EEG, las mejores precisiones estuvieron en el rango de frecuencia mu e inferior en beta, como se esperaba. Sin embargo, los resultados no fueron suficientemente precisos como para usarlas para el control de una aplicación.
Tesis

Knowing where and when to look is critical for effective performance of visually guided tasks. A gaze strategy termed the quiet eye (QE; the final gaze before the onset of a critical movement) is strongly associated with motor skill proficiency, with earlier and longer QE periods leading to improved visuomotor control. Children with poor motor proficiency, such as those with Developmental Coordination Disorder (DCD), have impairments in the pick-up and processing of visual information, translating into poorly coordinated movements. The purpose of this project therefore was to perform the first examination of the QE strategy in children of different motor coordination abilities and furthermore to investigate the efficacy of task-specific QE training (QET) to improve the skills of children with and without DCD beyond the effects of a standard coaching technique. Study 1 determined that children with low motor coordination had later, shorter QE durations in comparison to coordinated children and as a result, performed worse in a specified motor task (throwing and catching). Study 2 therefore performed two experiments aimed at developing an appropriate but brief QET protocol for children to improve their throwing and catching ability. These experiments found that typically developing children were able to increase their QE durations with QET and this was reflected in a durable improvement in their motor skill execution. The final study examined this QET intervention in children with DCD. This was the first application of QET in a clinical population, and found that children with DCD were able to improve their QE durations, and make robust changes to their visuomotor control. These studies associate a longer QE with motor skill proficiency in children, and provide an important adjunct to current therapeutic intervention for children with poorly developed motor skills.

En esta tesis se plantea el problema de control de posición de un sistema de una entrada y una salida (SISO), sujeto a cargas no lineales, empleando la metodología de Control Predictivo Basado en Modelo (MBPC). El sistema no lineal a controlar consiste de un servomotor DC de imán permanente con reducción, una etapa de potencia y una varilla acoplada al eje del motor. Los componentes del sistema de control de posición son: El actuador, que incluye un generador PWM (Modulación por Ancho de Pulso) y un amplificador PWM upo H; un servomotor DC; el bloque sensor, que incluye un codificador óptico incremental que sensa la posición angular y su sentido de giro; una interfaz de entrada/salida LAB-PC+; y, una PC Pentium. El software usado para la simulación es MATLAB y el lenguaje usado para la implementación del algoritmo de control de posición es O para la plataforma DOS. El proceso no lineal se modela usando ecuaciones que gobiernan su dinámica, que luego de ser linealizadas y discretizadas, se aplica la técnica de control predictivo para mostrar la respuesta del sistema controlado a referencias deseadas. Los resultados experimentales demuestran que el controlador predictivo es capaz de estabilizar la posición del servomotor en presencia de cargas no lineales variables y en presencia de restricciones a la entrada del sistema. En el apéndice A se estudia la técnica de control de posición polinomial usando la ecuación Diofantina, presentando los resultados de la simulación para efectos de comparación con el control predictivo
TThis thesis deals with the problem of controlling a nonlinear position process using the Model Based Predictive Control (MBPC). The single-input-single-output (SISO) process is a DC servomotor (with permanent magnet, conmutation brushes and gear reduction mechanism) driving a nonlinear load. Such a load, a metal road attached to the motor shaft, is able to roate (like a robot manipulator) in a plane perpendicular to the shaft, The components of the implemented position control system are: The actuator, that includes a PWM (Pulse Width Modulation) signal generator and a H-type PWM-amplifier: DC servo motor; the sensor block, that includes an incremental optical encoder that senses angular position and its sign; a Lab-PC+ Input/Output interface; and, a compatible PC with Pentium microprocesador. All the simulation tasks were developed using MATLAB and the required control software were written in c-code by DOS platform. The non linear process is modelled using linearized and discretized equations in order to apply the predictive control technic for different set-points signals. The experimental resulte demonstrates that the predictive controller is able to stabilize the position of the nonlinear load despite the presence of variable non-linear loads restrictions in the input process. Appendix A deals with the position control problem developed above, but using the Diofantina equation

Hybrid stepper motors are a common type of electric motor used throughout industry thanks to its low-cost, high torque at low speed and open loop positioning capabilities. However, a closed loop control is often required for industrial applications with high precision requirements. The closed loop control can also be used to lower the power consumption of the motor and ensure that stalls are avoided. It is quite common to utilise a large and costly position encoder or resolver to feedback the position signal to the control logic. This thesis has explored the possibility of using a low-cost position sensor based on Hall elements. Additionally, a sensorless estimation algorithm, using only stator winding measurements, has been investigated both as a competitive alternative and as a possible complement to the position sensor. The thesis work summarises and discusses previous research attempts to adequately measure or estimate and control the hybrid stepper motors position and load angle without using a typical encoder or resolver. Qualitative results have been produced through simulations prior to implementation and experimental testing. The readings from the position sensor is subject to noise, owing to its resolution and construction. The position signal has been successfully filtered, improving its accuracy from 0.56° to 0.25°. The output from the sensorless estimation algorithm is subject to non-linear errors caused by errors in phase voltage measurements and processing of velocity changes. However, the dynamics are reliable at constant speeds and could be used for position control.

In vector control of induction motors it is essential to know the parameters of the motor. Known approaches to this problem have some drawbacks. This thesis work is planned to develop solutions to the existing problems. The proposed solutions will be implemented and tested.

La capacité de coordonner efficacement nos yeux avec nos mains est déterminante pour le succès de nos actions quotidiennes. En outre la capacité de prédire les conséquences sensorielles de nos propres actions est cruciale pour nos habilités motrices. Dans ce travail, à l’aide d’une tâche dans laquelle les participants doivent suivre avec leurs yeux une cible visuelle bougée par leur main, nous nous intéressons aux mécanismes prédictifs sous-tendant la coordination œil-main. Dans une première étude utilisant un protocole d’adaptation à une rotation visuomotrice, nous montrons que ces mécanismes prédictifs peuvent être mis à jour indépendamment de notre capacité à effectuer des mouvements précis de la main. Dans l’étude suivante nous cherchons à déterminer l’effet de la préférence manuelle, et montrons que malgré des différences évidentes en termes de précision concernant le contrôle manuel, la capacité d’anticiper les conséquences visuelles de nos actions reste identique que la cible soit bougée par la main droite ou gauche. Enfin, grâce à la stimulation magnétique transcranienne, nous testons l'hypothèse selon laquelle ces mécanismes prédictifs utilisent des signaux efférents de la main issus du cortex moteur primaire (M1). Nos résultats montrent que si cette contribution existe, elle doit se faire nécessairement en amont de M1. Au bout du compte nous proposons que la coordination œil-main soit sous-tendue par des mécanismes prédictifs similaires pour nos deux mains, situés vraisemblablement en amont de M1, et pouvant être mis à jour indépendamment du contrôle de la main
The ability to coordinate efficiently eye and hand actions is central for humans in everyday activities. Furthermore it is argued that the ability to predict the sensory consequences of self-initiated movements is crucial for skilled motor behavior. Here by means of a task in which participants were asked to track with the eyes a visual target that was moved by their hand, we investigated the predictive mechanisms underlying eye-hand coordination. In a first study, using a protocol in which participants had to adapt to rotated hand visual feedback, we show that these predictive mechanisms can be updated independently of the ability to perform accurate hand movements. In a follow up study we tested the effect of hand dominance, and showed that, despite obvious differences in the accuracy of hand movement control, the ability to predict visual consequences of right and left hand actions was similar. Finally, by means of transcranial magnetic stimulation, we tested the hypothesis that those predictive mechanisms rely on hand efferent signals from the primary motor cortex (M1). However our results failed to support this view, and instead suggest that if such a contribution exists, it must be upstream of M1. Overall, we propose that eye-hand coordination relies on similar predictive mechanisms for both hands, possibly located upstream of M1, which can be updated independently of hand movement control

Les stratégies d’éco-conduite sont des approches dédiées matérialisées par des algorithmes capables d'utiliser des informations internes et externes liées à l’environnement du véhicule afin de créer des recommandations et/ou des limitations au conducteur et de générer automatiquement un profil d’usage pour le cas d’un véhicule autonome. Elles permettent notamment de réduire la consommation d'énergie et limiter les émissions de polluants, mais souvent n’intègrent pas directement l'autonomie et les performances requises par le conducteur en temps réel. Ces travaux de thèse visent à développer une stratégie d'éco-conduite adaptée aux motos électriques en intégrant les contraintes d’usage. En effet, la stratégie proposée utilise un contrôleur optimal basé sur une approche d’optimisation en temps réel. Cette dernière est orientée pour garantir que l'énergie disponible soit suffisante pour effectuer le trajet demandé, en adaptant le profil de vitesse suivant les conditions d’usage et les contraintes énergétiques. Pour ce faire, cette stratégie a mobilisé différents modèles considérant des contraintes multi-physiques (électriques, mécaniques, thermiques, ...etc.) des principaux éléments constituant la chaine de conversion : machine électrique, convertisseurs d’électronique de puissance et batterie, afin de tenir compte le comportement énergétique global. La stratégie proposée s’appuie sur un modèle non linéaire prédictif de commande (NMPC) associé à une optimisation unidimensionnelle non linéaire avec une fonction coût évolutive. Cette fonction intègre d’une manière progressive, au même niveau, plusieurs critères qui ont été départagés par une étude de sensibilité des coefficients de pondération, en tenant compte du temps de compilation pour satisfaire les besoins du temps réel. Ces travaux ont été validés en simulation et expérimentation sur un banc de test développé à échelle réduite. Cette validation a montré que la stratégie permet d'augmenter de 20% l'autonomie avec une limitation maximale de 30% de la vitesse et l’accélération pour les cas d’usage les plus contraignants (conduites dynamiques). En outre, la stratégie est capable de garantir la fin du trajet à 98% avec une erreur de distance inférieure à 1,5%, en présence de bruits de capteurs et d'actionneur
The eco-driving strategies are dedicated approaches based on algorithms capable to use external and internal vehicle data to create recommendations and/or limitations over the driver or to generate automatically a complete reference to be followed in the case of autonomous vehicle. They let to reduce the energy consummation and to limit the pollution emissions, but currently, their usage is not directly related to the autonomy and the performance required by the driver in real time. In this context, this thesis work proposes an Eco-Driving strategy suitable for electric motorcycle with usage limitations. In fact, this strategy uses an optimal controller able to make an online optimization process. This controller is oriented to ensure that the energy available is enough to complete a demanded trip and to adapt the speed profile according to the usage requirements and the energetic constraints. The developed strategy integrates dynamic models carrying out an optimization under multi-physic constraints (electric, mechanic, thermal …etc) present in the main elements of the power chain: electric machine, power electronics converters and battery. Those models let to make a global energy behavior representation. The NMPC optimization technic (non-linear model predictive controller) is supported on a non-linear mechanical model joined to a weight unidimensional non-linear optimization. This means that the NMPC cost function weights can evolve in function of energy behavior and external constraints. This multi-objective cost function integrates (in a progressive way) different behaviors that related to the energy consumption classified by a weighting sensitivity study. This process lets to find a good balance between the optimization goal and the compilation time to satisfy real-time needs. The developed approach has been validated in simulation and in experimental with a reduced scale developed test bench. The validation shows that the algorithm is able to increase around 20% the autonomy with a maximum limit of 30% of the speed and acceleration for the strict usage cases (dynamic driving). In addition, the algorithm is capable to ensure completing the travel in the 98% of cases with a distance error lower than 1.5% in the presence of sensors and actuator noises
Las estrategias de conducción ecológica son enfoques basados en algoritmos capacesde utilizar los datos del vehículo para crear recomendaciones sobre el conductor o generar una referencia completa a seguir en el caso de un vehículo autónomo. Estos, permiten reducir el consumo de energía pero actualmente su uso no está directamente relacionado con la autonomía y el rendimiento requerido por el conductor en tiempo real. En este contexto, este trabajo de tesis propone una estrategia de conducción ecológica adecuada para motocicletas eléctricas. De hecho, esta estrategia utiliza un controlador óptimo capaz de realizar un proceso de optimización online. Este controlador está orientado a garantizar que la energía disponible sea suficiente para completar un viaje demandado. Para cumplir esa meta, el control optimo adapta el perfil de velocidad de acuerdo con los requisitos de uso y las limitaciones energéticas. El enfoque desarrollado ha sido validado con un banco de pruebas desarrollado a escala reducida. La validación muestra que el algoritmo puede aumentar un 20 % la autonomía con una límitacion máxima del 30 % de la velocidad y aceleración para los casos de uso estricto. Además, el algoritmo es capaz de asegurar la capacidad para completar el recorrido en el 98 % de los casos con un error de distancia inferior al 1,5 %

碩士
國立聯合大學
電機工程學系碩士班
103
The objective of this thesis is to develop of the switched reluctance motor drive system and to use of the Texas Instruments produced TMS320F28335 digital signal processor control system including a set of general-purpose input and output ports, 16 channels of analog to digital converters (ADC), 12 channels of enhanced pulse width modulator (ePWM).The TI TMS320F28335 DSP control board can be not only set in accordance with the relevant user registers, automatically generate a PWM signal with a smooth drive and control the motor, but also simplified a large number of hardware circuits designs. First, the mathematical model of a switched reluctance motor is created, and then the use of a digital signal processor as the basis of a switched reluctance motor drive system is implemented. An incremental PI controller, a fuzzy controller, a fuzzy self-tuning proportional-integral controller, and a predictive controller, and a fuzzy self-tuning control gain predictive controller are proposed and implemented. Finally, a comparison and analysis of the advantages and disadvantages between these five controllers is presented.

碩士
國立臺灣科技大學
電機工程系
105
This thesis investigates the rotor position estimation and predictive controller for a three-phase DC excited flux-switching sensorless drive system. First, a high frequency voltage is injected into the excitation winding. Then, the high frequency current at the excitation winding and the high frequency equivalent q-axis current at the armature winding are measured to determine the estimated rotor position. After that, a speed-loop predictive controller is implemented to achieve quick transient responses, good tracking ability, and good external load rejection ability. In this paper, some hardware circuits are implemented with the software of the digital signal processor, TMS320F2808 to control the flux-switching drive system. Experimental results can validate the feasibility and correctness of the theoretical analysis for the sensorless drive system. Experimental result show the adjustable speed is from 10 r/min to 600 r/min, and the estimated position error is from -6 electric degrees to 6 electric degrees.

碩士
國立中興大學
機械工程學系
92
This thesis considers the system identification and infinite horizon stable predictive control (IHSPC) design for an AC induction motor-driven servo system. The RLS (recursive least squares) algorithm is used for obtaining the optimal parameters of a discrete-time linear estimation model with a constant bias term. Based on the estimated model, the IHSPC design methodology is adopted for synthesizing a stable predictive control law for the actual servo system. Finally, the control law is developed in the MATLAB/SIMULINK environment and implemented using a dSPACE DS1102 control board. Experimental results validate the feasibility of the suggested approach.

碩士
國立成功大學
電機工程學系
107
This dissertation presents an improved model predictive control (MPC) strategy to reduce the torque ripple and commutation frequency in conventional direct torque control (DTC) of the permanent magnet synchronous motor (PMSM). Nowadays, DTC has been widely used in industrial applications thanks to its simple structure and high dynamic performances. However, hysteresis controllers cause high torque ripple and variable switching frequency. In this novel method, hysteresis controllers and the switching table are replaced with a model predictive controller base online optimization for the selection of voltage space vector among the possible ones. Furthermore, a pre-selective process is designed to filter out the inappropriate voltage vectors to reduce the computational burden caused by the eight basic voltage space vectors. Then apply duty ratio modulation to determine the operating time of the selected voltage vector and zero voltage vector in one sample period for torque ripple reduction. By implementing the proposed DTC, torque ripple is reduced and the approximated switching frequency can be minimized to retain the advantages of a conventional DTC; meanwhile, the torque response is still quick. Both simulation and experimental results exhibit the effectiveness of this proposed approach.

Thesis in the scope of the PhD in Electrical and Computer Engineering, specialization in Energy, presented to the Faculty of Sciences and Technology of the University of Coimbra.
Nowadays, several types of electric motors are utilized in industrial applications, namely induction motors (IMs), permanent magnet synchronous motors (PMSMs) and synchronous reluctance motors (SynRMs). Owing to the high cost of PMSMs and due to the rotor losses of IMs, SynRMs can be considered an ideal choice for some applications. These motors have a simple structure, are robust, and have a low cost due to the absence of permanent magnets or windings in the rotor. To exploit the advantages of SynRM drives, an adequate control strategy is essential. In recent times, due to the development of fast and cheap microprocessors and FPGAs, the category of control strategies known as finite control set model predictive control (FCS-MPC) has attracted significant attention in both academia and industry. FCS-MPC has as main advantages, an intuitive and simple implementation, very fast dynamic response and the ability to tackle several constraints in a straightforward manner. Due to these advantages, it can be considered an ideal alternative to field-oriented control (FOC) and direct torque control (DTC) in high performance motor drives. In spite of its advantages, FCS-MPC has been barely proposed for the control of SynRM drives, especially if we consider that some applications require the drive system to operate in the full speed range. This thesis proposes three different FCS-MPC control strategies for high-performance SynRM drives. The first two control strategies combine the concepts of active flux and torque control in order to operate the SynRM in the constant torque region. The first control strategy, baptized as predictive active flux and torque control (PAFTC), regulates the active flux and the electromagnetic torque of the SynRM in an independent manner. It follows the standard implementation steps of FCS-MPC, namely by predicting the values of the state variables for all possible switching states of the inverter, and by using a cost function with a weighting factor which needs to be tuned. A second control approach, known as simplified PAFTC (S-PAFTC), is a simplified version of the PAFTC in the sense that the predictions of the state variables are replaced by the calculation of an equivalent reference voltage, performed only once in a sampling period. This procedure leads to a smaller computational time, when the control strategy is implemented in a digital control platform, and to the use of a cost function without any weighting factor, overcoming one of the challenging tasks in classical FCS-MPC strategies which is the choice of the optimal value(s) for the weighting factor(s). The simulation and experimental results obtained with these control strategies demonstrate the very good steady-state and dynamic response of the SynRM drive in the constant torque region. With the aim to safely operate the SynRM drive in the full speed range, while ensuring at the same time the exploitation of all its potentialities and limits, including its operation with optimal efficiency, a third control strategy, known as predictive load angle and stator flux control (PLASFC), is proposed for SynRM drives. The PLASFC, implemented in a stator flux reference frame, regulates the stator flux and the load angle of the SynRM in an independent manner. While the stator flux regulation is straightforward, the torque is regulated indirectly by controlling the load angle, bringing benefits in terms of a smooth transition between the different motor operating regions. Similarly to the S-PAFTC strategy, an equivalent reference voltage is calculated instead of predicting the values of the motor state variables for all possible switching states of the inverter, and the cost function does not include any weighting factor. In the PLASFC strategy, the SynRM is easily operated in the full speed range: constant torque region (including zero speed), constant power region and constant load angle region, the last two being part of what is usually known as field-weakening (FW) region. With this control strategy, the voltage, current and load angle limits are easily exploited by simple mathematical relations and saturation blocks. In addition, a loss minimization algorithm is developed and incorporated in this control strategy thus allowing to operate the SynRM with minimum copper losses for a given load torque. Furthermore, to improve the performance of the control system, some parameters namely the motor apparent inductances, are estimated online. Several simulation and experimental results presented demonstrate the excellent steady-state and dynamic performance of the SynRM drive when operating with the PLASFC strategy, thus clearly demonstrating the benefits of using FCS-MPC strategies in the field of electric drives in general and SynRM drives in particular.
Atualmente, diversos tipos de motores elétricos são utilizados em aplicações industriais, nomeadamente os motores de indução (IMs), os motores síncronos de ímanes permanentes (PMSMs) e os motores síncronos de relutância (SynRMs). Devido ao elevado custo dos PMSMs e às elevadas perdas no rotor dos motores de indução, os SynRMs podem ser considerados a escolha ideal para algumas aplicações. Estes motores possuem uma estrutura simples, são robustos e têm um baixo custo de fabrico devido à ausência de ímanes permanentes ou enrolamentos no rotor. De modo a explorar toda as vantagens dos acionamentos baseados em SynRMs, é essencial uma estratégia de controlo adequada. Recentemente, em virtude do desenvolvimento de microprocessadores e FPGAs mais rápidos e económicos, a categoria de controlo conhecida como controlo preditivo baseado em modelos de estados finitos (FCS-MPC) tem despertado um especial interesse no mundo académico e na indústria. O FCS-MPC tem várias vantagens, tais como uma implementação simples e intuitiva, uma rápida resposta dinâmica e a possibilidade de considerar várias restrições de uma forma direta. Devido a estas vantagens, o FCS-MPC pode ser considerado uma alternativa ideal ao controlo por orientação de campo (FOC) e ao controlo direto de binário (DTC) em acionamentos de alto desempenho. Apesar das suas vantagens, o FCS-MPC ainda tem sido pouco utilizado no controlo de acionamentos baseados em SynRMs, especialmente se considerar que algumas aplicações necessitam que o acionamento opere em toda a gama de velocidades. Esta dissertação propõe três estratégias de controlo FCS-MPC para acionamentos de alto desempenho baseados num SynRM. As duas primeiras estratégias de controlo combinam os conceitos do fluxo ativo e do controlo de binário, de modo a operar o SynRM na região de binário constante. A primeira estratégia, denominada controlo preditivo do fluxo ativo e de binário (PAFTC), regula o fluxo ativo e o binário eletromagnético do SynRM de forma independente. A estratégia PAFTC segue a estrutura padrão do FCS-MPC, uma vez que prevê os valores futuros das variáveis de estado para todos os estados de comutação possíveis do inversor, e utiliza uma função de custo com um peso que necessita de ser sintonizado. Uma segunda abordagem de controlo, denominada PAFTC simplificado (S-PAFTC), é uma versão simplificada do PAFTC uma vez que o cálculo das predições das variáveis de estado é substituído pelo cálculo das tensões de referência equivalentes, realizado apenas uma vez num período de amostragem. Esta estratégia de controlo possui um tempo de execução menor, quando implementada numa plataforma de controlo digital e, faz uso de uma função custo sem qualquer peso, ultrapassando um grande desafio das estratégias FCS-MPC clássicas, que é a escolha do(s) valor(es) ótimo(s) para o(s) peso(s). Os resultados de simulação e experimentais obtidos com estas estratégias de controlo mostram excelente desempenho do acionamento baseado no SynRM na região de binário constante, tanto em regime permanente como em regime dinâmico. Com o objetivo de operar o acionamento baseado no SynRM de forma segura em toda a gama de velocidades, e ao mesmo tempo assegurar que todas as suas potencialidades e limites são explorados, incluindo uma operação com eficiência ótima, uma terceira estratégia de controlo, conhecida como controlo preditivo do ângulo de carga e fluxo estatórico (PLASFC), é proposta para acionamentos baseados em SynRMs. A estratégia de controlo PLASFC, implementada no referencial do fluxo estatórico, controla o fluxo estatórico e o ângulo de carga do SynRM de forma independente. Enquanto que a regulação do fluxo estatórico é direta, a regulação do binário é realizado de forma indireta através do controlo do ângulo de carga, o que conduz a uma transição suave entre as diferentes regiões de operação do motor. Tal como na estratégia S-PAFTC, as tensões de referência equivalentes são calculadas ao invés de prever os valores futuros das variáveis de estado do motor para todas os estados de comutação do inversor possíveis, e a função custo não inclui qualquer peso. Na estratégia PLASFC, o SynRM é facilmente operado em toda a gama de velocidades: região de binário constante (incluindo a velocidade zero), região de potência constante e região de ângulo de carga constante, sendo que as últimas duas regiões pertencem à região normalmente designada por região de campo enfraquecido (FW). Com esta estratégia de controlo, os limites de tensão, corrente e ângulo de carga são facilmente explorados através de relações matemáticas simples e blocos de saturação. Adicionalmente, um algoritmo de minimização de perdas é desenvolvido e incorporado nesta estratégia de controlo, permitindo que o SynRM opere com perdas no cobre mínimas para um dado binário de carga. Além disso, para melhorar o desempenho do sistema de controlo, alguns parâmetros tais como as indutâncias aparentes do motor são estimadas em tempo real. Por fim, são apresentados múltiplos resultados de simulação e experimentais que demonstram um excelente desempenho do acionamento baseado no SynRM quando operado através da estratégia PLASFC tanto em regime permanente quanto em regime dinâmico, demonstrando claramente os benefícios da utilização das estratégias FCS-MPC no campo dos acionamentos elétricos em geral e, particularmente, nos acionamentos baseados em SynRMs.

碩士
國立交通大學
電控工程研究所
102
In the network control systems (NCS), both data dropout and time delay greatly affect control performance and stability. In this study, the perfect delay compensation (PDC) is applied to eliminate the network-induced delay effect on the NCS with an AC servo motor, Ethernet, Zigbee, CAN bus. Moreover, applying the least square algorithm and real-time estimation of the transition probability for data dropout, the intelligent message estimator (IME) in a switching mechanism based on the estimated transition probability is developed to reliably estimate the missing message with different dropout distributions. Furthermore, the data-base predictive controller (DPC) is implemented on NCS in this Thesis to predict the best control signals by optimizing system performance. By combining the IME and the predicted signal from DPC, the automatic switching mechanism of IME under different data dropout rates is thus obtained. Finally, the integrated compensator combining all the PDC, IME and DPC leads to satisfactory compensation results to deal with both the time delay and the data dropout in NCS.

碩士
國立成功大學
機械工程學系碩博士班
94
The aim of this paper is to apply Model Predictive Control (MPC) to the Parallel-type Double Inverted Pendulum (PDIP). Control of the PDIP is more difficult among the inverted pendulum family. Because the different lengths of the two pendulums give them distinct natural frequencies and the stoke length is limited. Besides, friction is not homogenously distributed on the track. Please bear in mind that one cannot achieve good performance if only state feedback is used. Therefore, we proposed a cascade structure where the inner loop was formed via state feedback and MPC directed the outer loop to enhance position control of the linear motor. In this work, a positive feedback control combined with energy-based control is adopted to swing up the PDIP sequentially, and then is switched to balance control. From simulation and experimental results, the proposed control scheme was successfully applied to the PDIP. Compared with conventional state feedback control, position errors could be reduced by MPC, which overcome the requirement of precise friction model needed in state feedback applications.

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores
Nowadays, Electric Vehicles are emerging as the most sustainable alternative to support the expected rise in the number of vehicles in circulation around the world, and to reduce the impact of the transportation sector on the environment. However, this is a technology that still has some limitations that restrict its mainstream adoption. Typically, an Electric Vehicle has a motor drive system and an on-board battery charger that allows charging its battery pack almost anywhere, as long as there is an electrical outlet available. However, this is usually a low-power charger in order to optimize the space and weight on-board the vehicle. As a result, this type of charging typically takes a couple of hours. The purpose of this MSc. Thesis was the development of a unified power electronics converter, capable of performing the roles of drive the electrical machine of an Electric Vehicle and also charging its battery pack, so as to optimize the space and weight of the power electronics components on-board the vehicle while also providing a faster charging operation. The first part of this MSc. Thesis consisted in the study of the state of art of the unified hardware solutions proposed, based on the use of the power electronics components of the motor drive system during the battery charging operation, since both operation modes cannot be performed simultaneously, except for regenerative breaking. Also the respective control algorithms that allow perform each operation mode, according with the solution proposed, were studied. The second part consisted in simulating the proposed unified solution and implementing a proof-of-concept prototype. In the proposed solution the battery charger is based on the use of a three-phase Voltage Source Inverter and the windings of a Brushless DC machine. With respect to the control algorithms, for the motor drive mode the Field-Oriented Control was chosen, while for the battery charging mode two control algorithms were chosen (one for single-phase charging and the other for three-phase charging), based on the Model Predictive Control. The obtained results validate the proposed solution. However, in the case of the electrical machine used in this MSc. Thesis, the values of the inductances of its windings compromise its use as an input filter.
Atualmente os Veículos Elétricos surgem como a alternativa mais sustentável perante o aumento expectável do número de veículos em circulação no mundo e por forma a reduzir o impacto ambiental do sector do transporte. Contudo, esta é ainda uma tecnologia com algumas limitações, que ainda não permitiram a sua aquisição em maior escala. Tipicamente um Veículo Elétrico possui um sistema de tração e um sistema de carregamento, que permite carregar as suas baterias em praticamente qualquer local, desde que haja disponível uma tomada ligada à rede elétrica. No entanto, este sistema de carregamento tem normalmente uma potência instalada baixa, por forma a otimizar o espaço e peso ocupados no interior do veículo. Como resultado, este tipo de carregamento demora tipicamente algumas horas. Esta Dissertação de Mestrado teve como objetivo o desenvolvimento de um conversor unificado, capaz de controlar a máquina elétrica usada para a tração de um Veículo Elétrico e de carregar as suas baterias, permitindo otimizar ainda mais o espaço e peso ocupados pelos componentes de eletrónica de potência instalados no veículo e possibilitar ainda carregamentos mais rápidos. A primeira parte desta Dissertação consistiu num estudo do estado da arte de sistemas de hardware unificados, baseados na utilização dos componentes de eletrónica de potência do sistema de tração durante o modo de carregamento das baterias, tendo em conta que as duas operações não podem ser realizadas em simultâneo, exceto para travagem regenerativa. Também foram estudados os algoritmos de controlo que permitem executar cada uma das operações, de acordo com a topologia proposta. A segunda parte consistiu na simulação da solução proposta e na implementação de um protótipo para demonstração da funcionalidade. Nesta solução proposta, o sistema de carregamento baseia-se na utilização de um inversor trifásico do tipo Voltage Source Inverter e dos enrolamentos de uma máquina elétrica do tipo Brushless DC. Em relação aos algoritmos de controlo, para o modo de tração foi selecionado o Controlo por Orientação de Campo (Field-Oriented Control), enquanto que para o modo de carregamento foram selecionados dois algoritmos (um para carregamento monofásico e outro para trifásico), baseados no Controlo Preditivo (Model Predictive Control). Os resultados obtidos permitiram validar a solução proposta. Contudo, os baixos valores de indutância da máquina elétrica usada comprometem o seu uso como filtro de entrada.

Experience Mapping based Prediction Control (EMPC) is a new type of controller presented in literature, which is based on the concept of Human Motor Control (HMC). During the developmental phase, called the initial learning phase, the controller records the experience in a knowledge base, through online interactions with the system to be controlled. This knowledge base created using the experience maps is termed as Experience Mapped Knowledge Base (EMK). The controller envisages the development of EMK only through interaction with the system, without the need for knowledge of the detailed plant model. The EMPC controls the system through prediction of actions based on the mapped experiences of EMK. Depending on the nature of control required for the system chosen, various strategies can be used to achieve control using the EMK. The above controller has previously been utilized for motion control applications. In the present work an effort has been made to study the suitability of the EMPC for the voltage regulation of switching converters. The plant chosen for the control study is a discontinuous conduction mode (DCM) buck converter. The parameter to be monitored for the purpose of control is the load voltage. The control input from the EMPC to the converter is a duty ratio value based pulse-width modulated (PWM) signal. Two strategies of control have been proposed: steady state control and transient control. Steady state control action maintains the steady state output voltage at the required value for a given load. The transient control action is used to improve the transient performance of the system. Iterative predictive action and iterative transient actions are used to facilitate convergence of the output voltage to within the required range in presence of non-linearities and uncertainties in the system. Impulse action is introduced to further improve the transient performance of the system. The EMPC is compared a proportional-integral (PI) controller for the given DCM buck system.

Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia
O principal objetivo deste trabalho consistiu no desenvolvimento, implementação e teste, tanto a nível de hardware como de software, de um sistema de tração do veículo elétrico do IT - Pólo de Coimbra, baseado num motor síncrono de relutância (SynRM), e comandado a partir da plataforma de controlo digital dSPACE MicroAutobox II.O Capítulo 1, de forma introdutória, expõe um enquadramento geral do tema no qual otrabalho se desenvolveu. É apresentada a história dos veículos elétricos e o seu desenvolvimento ao longo do tempo, destacando as principais vantagens face às alternativas existentes no mercado, que evidenciam a motivação para a realização deste trabalho. É ainda abordado o projeto no qual está inserida a dissertação, destacando os principais componentes utilizados, desde o SynRM, o sistema de controlo preditivo utilizado e a plataforma Microautobox II, explicando quais as razões que levaram à sua utilização.É efetuada, no Capítulo 2, uma caracterização do modelo do motor utilizado, destacandoas suas principais vantagens comparativamente a outros motores convencionais existentes na indústria. Nesta secção, são também apresentados detalhes relativos à sua construção, estrutura e fenómenos de saturação magnética e saturação magnética cruzada, bem como as consequências que estes fenómenos impõem no sistema de controlo.O principal objetivo do Capítulo 3 consiste na apresentação da estratégia de controloutilizada no acionamento elétrico do veículo, justificando a opção pela estratégia implementada e apresentando-a de forma detalhada.O Capítulo 4 introduz a plataforma de controlo Microautobox II definindo-a eapresentando-a com as diferentes placas que a constituem. Aborda as especificações inerentes de cada placa, apresentando todas as alterações realizadas no modelo de controlo, construído previamente em ambiente Simulink, de modo a fazer corresponder os blocos implementados no modelo com as entradas e saídas utilizadas, para o correto funcionamento do sistema de tração.Inicialmente no Capítulo 5 é apresentada a montagem experimental, de modo a identificaros diferentes componentes do sistema de tração, no entanto o principal foco deste capítulo recaí na apresentação dos resultados obtidos a partir dos diferentes ensaios realizados.Para concluir, segue-se o capítulo 6 onde são expostas as conclusões deste trabalho,acompanhadas de sugestões de implementações futuras.
The main objective of this work is the development, implementation and test, at the level of both hardware and software, of the traction drive system of the electric vehicle of IT – Polo de Coimbra, based on a synchronous reluctance motor (SynRM), and commanded with a dSPACE MicroAutobox II digital control platform.Chapter 1, of introductory nature, sets out a general framework of the theme on which the work has been developed. This chapter presents the history of electric vehicles and their development over time, highlighting the main advantages over the alternatives in the market, which show the motivation to carry out this work. It is also approached the project in which the thesis is inserted, highlighting the main components used, from the SynRM, such as the predictive control system used and the platform Microautobox II, explaining the reasons that led to its use.In Chapter 2 is performed a characterization of the SynRM model used, highlighting someof its main advantages compared to other conventional motors in the industry. In this section, details are also presented concerning their construction and structure and phenomena of magnetic saturation and cross-magnetic saturation, as well as the consequences they have on the control system.The main goal of Chapter 3 is to present the control strategy used in the traction drive of the electric vehicle, justifying the option for the implemented strategy and presenting it in detail.Chapter 4 introduces the Microautobox II control platform by defining and presenting itwith the different boards that constitute it. It discusses the inherent specifications of each board, presenting all the changes made in the control model, previously built in Simulink environment, in order to match the blocks implemented in the model with the inputs and outputs used, for the correct operation of the traction system.Initially in Chapter 5 the experimental setup is presented, in order to identify the different components of the traction system, however the main focus of this chapter lies in the presentation of the results obtained from the different tests performed.To conclude, chapter 6 presents the conclusions of this work, accompanied by suggestions for future implementations.