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Umemura, Yoshio, Noboru Sakamoto, and Yuto Yuasa. "Optimal Control Designs for Systems with Input Saturations and Rate Limiters." IEEE, 2010. http://hdl.handle.net/2237/14447.
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Jha, Sumit Kumar. "Filter-based adaptive optimal control designs for uncertain linear time invariant systems." Thesis, IIT Delhi, 2019. http://eprint.iitd.ac.in:80//handle/2074/8062.
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Bortnick, Steven M. "Optimal block designs for simultaneous comparison of test treatments with a control /." The Ohio State University, 1999. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488192447429755.
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Mohagheghi, Salman. "Adaptive Critic Designs Based Neurocontrollers for Local and Wide Area Control of a Multimachine Power System with a Static Compensator." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/16216.
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Modern power systems operate much closer to their stability limits than before. With the introduction of highly sensitive industrial and residential loads, the loss of system stability becomes increasingly costly. Reinforcing the power grid by installing additional transmission lines, creating more complicated meshed networks and increasing the voltage level are among the effective, yet expensive solutions. An alternative approach is to improve the performance of the existing power system components by incorporating more intelligent control techniques.
This can be achieved in two ways: introducing intelligent local controllers for the existing components in the power network in order to employ their utmost capabilities, and implementing global intelligent schemes for optimizing the performance of multiple local controllers based on an objective function associated with the overall performance of the power system. Both these aspects are investigated in this thesis.
In the first section, artificial neural networks are adopted for designing an optimal nonlinear controller for a static compensator (STATCOM) connected to a multimachine power system. The neurocontroller implementation is based on the adaptive critic designs (ACD) technique and provides an optimal control policy over the infinite horizon time of the problem. The ACD based neurocontroller outperforms a conventional controller both in terms of improving the power system dynamic stability and reducing the control effort required.
The second section investigates the further improvement of the power system behavior by introducing an ACD based neurocontroller for hierarchical control of a multimachine power system. The proposed wide area controller improves the power system dynamic stability by generating optimal control signals as auxiliary reference signals for the synchronous generators automatic voltage regulators and the STATCOM line voltage controller. This multilevel hierarchical control scheme forces the different controllers throughout the power system to optimally respond to any fault or disturbance by reducing a predefined cost function associated with the power system performance.
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Park, Jung Wook. "Adaptive/optimal neurocontrol based on adaptive critic designs for synchronous generators and facts devices in power systems using artificial neural networks." Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/13872.
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Liang, Jiaqi. "Wind energy and power system interconnection, control, and operation for high penetration of wind power." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/47570.
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High penetration of wind energy requires innovations in different areas of power engineering. Methods for improving wind energy and power system interconnection, control, and operation are proposed in this dissertation. A feed-forward transient compensation control scheme is proposed to enhance the low-voltage ride-through capability of wind turbines equipped with doubly fed induction generators. Stator-voltage transient compensation terms are introduced to suppress rotor-current overshoots and torque ripples during grid faults. A dynamic stochastic optimal power flow control scheme is proposed to optimally reroute real-time active and reactive power flow in the presence of high variability and uncertainty. The performance of the proposed power flow control scheme is demonstrated in test power systems with large wind plants. A combined energy-and-reserve wind market scheme is proposed to reduce wind production uncertainty. Variable wind reserve products are created to absorb part of the wind production variation. These fast wind reserve products can then be used to regulate system frequency and improve system security.
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Ma, Yuan. "Optimal mems plate design and control for large channel count optical switches." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/2071.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.Thesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Godoy, Rodrigo Juliani Corrêa de. "Plantwide control: a review and proposal of an augmented hierarchical plantwide control design technique." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-07112017-140120/.
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The problem of designing control systems for entire plants is studied. A review of previous works, available techniques and current research challenges is presented, followed by the description of some theoretical tools to improve plantwide control, including the proposal of an augmented lexicographic multi-objective optimization procedure. With these, an augmented hierarchical plantwide control design technique and an optimal multi-objective technique for integrated control structure selection and controller tuning are proposed. The main contributions of these proposed techniques are the inclusion of system identification and optimal control tuning as part of the plantwide design procedure for improved results, support to multi-objective control specifications and support to any type of plant and controllers. Finally, the proposed techniques are applied to industrial benchmarks to demonstrate and validate its applicability.O problema de projetar sistemas de controle para plantas inteiras é estudado. Uma revisão de trabalhos anteriores, técnicas disponíveis e atuais desafios de pesquisa é apresentada, seguida da descrição de algumas ferramentas teóricas para melhorar o controle plantwide, incluindo a proposta de um procedimento de otimização multi-objetivo lexicográfico aumentado. Com tais elementos, são propostas uma nova técnica hierárquica aumentada de projeto de sistemas de controle plantwide e uma técnica multi-objetivo para seleção de estrutura de controlador integrada à sintonia ótima do controlador. As principais contribuições das técnicas propostas são a inclusão de identificação de sistemas e sintonia ótima de controladores como parte do procedimento de projeto de controle plantwide para melhores resultados, suporte a especificações multi-objetivo e suporte a quaisquer tipos de plantas e controladores. Finalmente, as técnicas propostas são aplicadas a benchmarks industriais para demonstrar e validar sua aplicabilidade.
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Carlsson, Jesper. "Optimal Control of Partial Differential Equations in Optimal Design." Doctoral thesis, KTH, Numerisk Analys och Datalogi, NADA, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9293.
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This thesis concerns the approximation of optimally controlled partial differential equations for inverse problems in optimal design. Important examples of such problems are optimal material design and parameter reconstruction. In optimal material design the goal is to construct a material that meets some optimality criterion, e.g. to design a beam, with fixed weight, that is as stiff as possible. Parameter reconstrucion concerns, for example, the problem to find the interior structure of a material from surface displacement measurements resulting from applied external forces. Optimal control problems, particularly for partial differential equations, are often ill-posed and need to be regularized to obtain good approximations. We here use the theory of the corresponding Hamilton-Jacobi-Bellman equations to construct regularizations and derive error estimates for optimal design problems. The constructed Pontryagin method is a simple and general method where the first, analytical, step is to regularize the Hamiltonian. Next its Hamiltonian system is computed efficiently with the Newton method using a sparse Jacobian. An error estimate for the difference between exact and approximate objective functions is derived, depending only on the difference of the Hamiltonian and its finite dimensional regularization along the solution path and its L² projection, i.e. not on the difference of the exact and approximate solutions to the Hamiltonian systems. Another treated issue is the relevance of input data for parameter reconstruction problems, where the goal is to determine a spacially distributed coefficient of a partial differential equation from partial observations of the solution. It is here shown that the choice of input data, that generates the partial observations, affects the reconstruction, and that it is possible to formulate meaningful optimality criteria for the input data that enhances the quality of the reconstructed coefficient. In the thesis we present solutions to various applications in optimal material design and reconstruction.Denna avhandling handlar om approximation av optimalt styrda partiella differentialekvationer för inversa problem inom optimal design. Viktiga exempel på sådana problem är optimal materialdesign och parameterskattning. Inom materialdesign är målet att konstruera ett material som uppfyller vissa optimalitetsvillkor, t.ex. att konstruera en så styv balk som möjligt under en given vikt, medan ett exempel på parameterskattning är att hitta den inre strukturen hos ett material genom att applicera ytkrafter och mäta de resulterande förskjutningarna. Problem inom optimal styrning, speciellt för styrning av partiella differentialekvationer,är ofta illa ställa och måste regulariseras för att kunna lösas numeriskt. Teorin för Hamilton-Jacobi-Bellmans ekvationer används här för att konstruera regulariseringar och ge feluppskattningar till problem inom optimaldesign. Den konstruerade Pontryaginmetoden är en enkel och generell metod där det första analytiska steget är att regularisera Hamiltonianen. I nästa steg löses det Hamiltonska systemet effektivt med Newtons metod och en gles Jacobian. Vi härleder även en feluppskattning för skillnaden mellan den exakta och den approximerade målfunktionen. Denna uppskattning beror endast på skillnaden mellan den sanna och den regulariserade, ändligt dimensionella, Hamiltonianen, båda utvärderade längst lösningsbanan och dessL²-projektion. Felet beror alltså ej på skillnaden mellan den exakta och denapproximativa lösningen till det Hamiltonska systemet. Ett annat fall som behandlas är frågan hur indata ska väljas för parameterskattningsproblem. För sådana problem är målet vanligen att bestämma en rumsligt beroende koefficient till en partiell differentialekvation, givet ofullständiga mätningar av lösningen. Här visas att valet av indata, som genererarde ofullständiga mätningarna, påverkar parameterskattningen, och att det är möjligt att formulera meningsfulla optimalitetsvillkor för indata som ökar kvaliteten på parameterskattningen. I avhandlingen presenteras lösningar för diverse tillämpningar inom optimal materialdesign och parameterskattning.
QC 20100712
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Cardoso, de Castro Nicolas. "Energy-aware control and communication co-design in wireless net-worked control systems." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENT113/document.
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L'énergie est une ressource clé dans les systèmes commandés en réseau, en particulier dans les applications concernant les réseaux sans fil. Cette thèse étudie comment économiser l'énergie dans les capteurs sans fil avec une co-Conception contrôle et communication. Cette thèse examine les techniques et les approches existantes qui sont utilisées pour économiser l'énergie d'un point de vue de la communication et du contrôle. Cet étude est organisée selon une architecture de communication par couches couvrant de bas en haut les couches Physique, Liaison, Réseau, et Application. Puis, à partir de la conclusion que la puce radio est un important consommateur d'énergie, une loi conjointe de gestion des modes radio et de contrôle en boucle fermée est établie. La gestion des modes radio exploite les capacités de la puce radio à communter dans des modes de basses consommation pour économiser l'énergie, et d'adapter la puissance de transmission aux conditions du canal. Il en résulte un système de contrôle basé sur des événements où le système fonctionne en boucle ouverte à certains moments. Un compromis naturel apparaît entre l'économie d'énergie et les performances de contrôle. La loi conjointe est établie avec une formulation de contrôle optimal utilisant la Programmation Dynamique. Cette thèse résout le problème optimal dans les deux cas d'horizon infini et fini. La stabilité du système en boucle fermée est étudiée avec la formulation Input-To-State Stability (ISS). La principale conclusion de cette thèse, également illustrée dans la simulation, est que la conception à travers différentes couches dans les systèmes commandés en réseau est essentielle pour économiser l'énergie dans les noeuds sans filEnergy is a key resource in Networked Control Systems, in particular in applications concerning wireless networks. This thesis investigates how to save energy in wireless sensor nodes with control and communication co-Design. This thesis reviews existing techniques and approaches that are used to save energy from a communication and a control point of view. This review is organized according to the layered communication architecture covering from bottom to top the Physical, Data Link, Network, and Application layers. Then, from the conclusion that the radio chip is an important energy consumer, a joint radio-Mode management and feedback law policy is derived. The radio-Mode management exploits the capabilities of the radio chip to switch to low consuming radio-Modes to save energy, and to adapt the transmission power to the channel conditions. This results in an event-Based control scheme where the system runs open loop at certain time. A natural trade-Off appears between energy savings and control performance. The joint policy is derived in the framework of Optimal Control with the use of Dynamic Programming. This thesis solves the optimal problem in both infinite and finite horizon cases. Stability of the closed loop system is investigated with Input-To-State Stability framework. The main conclusion of this thesis, also shown in simulation, is that cross-Layer design in Networked Control System is essential to save energy in the wireless nodes
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Yiu, Ka Fai Cedric. "Aerodynamic design via optimal control theory." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317867.
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Ting, Chao-Ping. "Optical designs for treatment-control comparison /." The Ohio State University, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487335992904001.
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Hunt, K. J. "Stochastic optimal control theory with application in self-tuning control." Thesis, University of Strathclyde, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382399.
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Müller, Matias. "Regret and Risk Optimal Design in Control." Licentiate thesis, KTH, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-248997.
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Engineering sciences deal with the problem of optimal design in the face of uncertainty. In particular, control engineering is concerned about designing policies/laws/algorithms that sequentially take decisions given unreliable data. This thesis addresses two particular instances of optimal sequential decision making for two different problems. The first problem is known as the H∞-norm (or l2-gain, for LTI systems) estimation problem, which is a fundamental quantity in control design through the small gain theorem. Given an unknown system, the goal is to find the maximum l2-gain which, in a model-free approach, involves solving a sequential input design problem. The H∞-norm estimation problem (or simply "gain estimation problem") is cast as the composition of a multi-armed bandit problem generating data, and an optimal estimation problem given that data. It is shown that the separation of the gain estimation problem into these two sub-problems is optimal in a mean-square sense, as the expected estimation error asymptotically matches the Cramér-Rao lower bound. In the second part of the thesis, we address the problem of risk-coherent optimal control design for disturbance rejection under uncertainty, where optimality is studied from an H2 and an H∞ sense. We consider a parametric model for the plant and the noise spectrum, where the modeling error between the model and the real system is uncertain. This uncertainty is condensed in a probability density function over the different realizations of the parameters defining the model. We use this information to design a controller that minimizes the risk of falling into poor closed-loop performance within a financial theory of risk framework. A systematic approach for the design of H2- and H∞-optimal controllers is proposed in terms of a quadratically-constrained linear program and a semi-definite program, respectively. An interesting application to H2-optimal design under covert attacks is also developed.QC 20190411
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Tsai, Mi-Ching. "Super-optimal control system design for multivariable plants." Thesis, University of Oxford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238170.
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Iolov, Alexandre V. "Parameter Estimation, Optimal Control and Optimal Design in Stochastic Neural Models." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34866.
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This thesis solves estimation and control problems in computational
neuroscience, mathematically dealing with the first-passage times of diffusion
stochastic processes. We first derive estimation algorithms for model parameters
from first-passage time observations, and then we derive algorithms for the
control of first-passage times. Finally, we solve an optimal design
problem which combines elements of the first two: we ask how to elicit
first-passage times such as to facilitate model estimation based on said
first-passage observations.
The main mathematical tools used are the Fokker-Planck partial differential
equation for evolution of probability densities, the Hamilton-Jacobi-Bellman
equation of optimal control and the adjoint optimization principle from optimal
control theory.
The focus is on developing computational schemes for the
solution of the problems. The schemes are implemented and are tested for a wide
range of parameters.
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Alhejji, Ayman Khalid. "Dynamic Neural Network-based Adaptive Inverse Optimal Control Design." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/891.
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This dissertation introduces a Dynamical Neural Network (DNN) model based adaptive inverse optimal control design for a class of nonlinear systems. A DNN structure is developed and stabilized based on a control Lyapunov function (CLF). The CLF must satisfy the partial Hamilton Jacobi-Bellman (HJB) equation to solve the cost function in order to prove the optimality. In other words, the control design is derived from the CLF and inversely achieves optimality when the given cost function variables are determined posterior. All the stability of the closed loop system is ensured using the Lyapunov-based analysis. In addition to structure stability, uncertainty/ disturbance presents a problem to a DNN in that it could degrade the system performance. Therefore, the DNN needs a robust control against uncertainty. Sliding mode control (SMC) is added to nominal control design based CLF in order to stabilize and counteract the effects of disturbance from uncertain DNN, also to achieve global asymptotic stability. In the next section, a DNN observer is considered for estimating states of a class of controllable and observable nonlinear systems. A DNN observer-based adaptive inverse optimal control (AIOC) is needed. With weight adaptations, an adaptive technique is introduced in the observer design and its stabilizing control. The AIOC is designed to control a DNN observer and nonlinear system simultaneously while the weight parameters are updated online. This control scheme guarantees the quality of a DNN's state and minimizes the cost function. In addition, a tracking problem is investigated. An inverse optimal adaptive tracking control based on a DNN observer for unknown nonlinear systems is proposed. Within this framework, a time-varying desired trajectory is investigated, which generates a desired trajectory based on the external inputs. The tracking control design forces system states to follow the desired trajectory, while the DNN observer estimates the states and identifies unknown system dynamics. The stability method based on Lyapunov-based analysis is guaranteed a global asymptotic stability. Numerical examples and simulation studies are presented and shown for each section to validate the effectiveness of the proposed methods.
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Okura, Yuki. "Trajectory Design Based on Robust Optimal Control and Path Following Control." Kyoto University, 2019. http://hdl.handle.net/2433/242499.
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付記する学位プログラム名: デザイン学大学院連携プログラムKyoto University (京都大学)
0048
新制・課程博士
博士(工学)
甲第21761号
工博第4578号
新制||工||1713(附属図書館)
京都大学大学院工学研究科航空宇宙工学専攻
(主査)教授 藤本 健治, 教授 泉田 啓, 教授 太田 快人
学位規則第4条第1項該当
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Fleming, Andrew. "Real-time optimal slew maneuver design and control." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1197.
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Approved for public release; distribution in unlimited.This thesis considers the problem of time-optimal spacecraft slew maneuvers. Since the work of Bilimoria and Wie it has been known that the time-optimal reorientation of a symmetric rigid body was not the eigenaxis maneuver once thought to be correct. Here, this concept is extended to axisymmetric and asymmetric rigid body reorientations with idealized independent torque generating devices. The premise that the time-optimal maneuver is not, in general, an eigenaxis maneuver, is shown to hold for all spacecraft configurations. The methodology is then extended to include spacecraft control systems employing magnetic torque rods, a combination of pitch bias wheel with magnetic torque rods, and finally to control systems employing single gimbal control moment gyros. The resulting control solutions, designed within the limitations of the actuators, eliminate the requirement to avoid actuator singularities. Finally, by employing sampled-state feedback the viability of real-time optimal closed loop control is demonstrated.
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Fleming, Andrew. "Real-time optimal slew maneuver design and control." Monterey, Calif. : Naval Postgraduate School, 2008. http://handle.dtic.mil/100.2/ADA477384.
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Thesis (Astronautical Engineer and M.S. in Astronautical Engineering)--Naval Postgraduate School, June 2008.Thesis Advisor(s): Ross, I. Michael. "December 2004." Description based on title screen as viewed on September 30, 2008. Includes bibliographical references. Also available in print.
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Richards, David M. (David Michael). "l1-optimal control : solution software and design examples." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/14202.
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Qin, Li. "Uncertainty, robust control and optimal monetary policy design." Université Louis Pasteur (Strasbourg) (1971-2008), 2008. http://www.theses.fr/2008STR1EC06.
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Cette thèse étudie l'influence de la prise en compte de l'incertitude sur la conduite de politiques monétaires. En adoptant le cadre d'analyse du contrôle robuste développé par Hansen et Sargent (2003), ce travail examine les comportements des autorités monétaires et des agents privés sous l'influence de différentes sources d'incertitudes. Notre recherche démontre que la prise en compte de l'incertitude de modèle conduit la banque centrale à réagir de manière plus active en ajustant le taux d'intérêt. Cependant, dans une économie ouverte, l'ampleur de cet ajustement diminue avec le degré d'ouverture de l’économie. Par ailleurs, une transparence accrue sur l'objectif de la banque centrale a pour conséquence d'atténuer la variation des variables macroéconomiques consécutive à la prise en compte des éventuelles spécifications erronées. Il est donc recommandable de révéler les informations concernant les préférences des banquiers centraux, y compris leurs estimations sur le degré de l'incertitude de modèleThis thesis analyze the conduct of monetary policy in the presence of uncertainty. By adopting the framework proposed by Hansen and Sargent (2003), we analyze the behaviors of monetary authorities and private agents when faced with various sources of uncertainty, as well as their consequences in terms of macroeconomic performances. Our work shows that, in order to guard against the possibly catastrophic results of the worst-case scenario, central bankers have to react in an active manner, by manipulating the interest rate. However, in an open economy, the magnitude of this adjustment decreases with the degree of openness. Also, greater transparency of the central bank's objectives, by reducing preference uncertainty, will attenuate the variations of macroeconomic variables that follow the consideration of possible erroneous specifications. It is thus advisable to reveal informations about the central bankers' preferences, including their own estimates of the degree of model uncertainty
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Sahu, Reetik Kumar. "Optimal reservoir operation using stochastic model predictive control." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104561.
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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2016.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 61-65).
Dynamical systems are subjected to various random external forcings that complicate theie control. In order to achieve optimal performance, these systems need to continually adapt to external disturbances in real time. This capability is provided by feedback based control strategies that derive an optimal control from the current state of the system. Model Predictive Control(MPC) is one such feedback-based technique. This thesis explores the application of a stochastic version of MPC to a reservoir system. The reservoir system is designed to maximize the revenue generated from the hydroelectricity while simultaneously obeying several exogenous constraints. An ensemble based version of the stochastic MPC technique is studied and applied to the reservoir to determine the optimal water release strategies. Further analysis is performed to understand the sensitivity of different parameters in the MPC technique.
by Reetik Kumar Sahu.
S.M.
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Parkes, Norman Ernest. "Polynomial based computer aided design of optimal control systems." Thesis, Queen's University Belfast, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333830.
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Williams, R. A. "Comparison of classical and optimal active suspension control systems." Thesis, Loughborough University, 1986. https://dspace.lboro.ac.uk/2134/25139.
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British Rail has been designing active suspensions for some 16 years, starting with tilt systems for the Advanced Passenger train. These have been designed using classical control techniques requiring a combination of experience, intuition and frequency response stability techniques, such as Nichols' plots. In order to see if a more systematic approach to control system design could produce improvements in performance and implementation the current investigation was instigated in which controllers designed using classical techniques are compared with controllers designed using linear optimal control theory. The active suspension used for the investigation was an Electro Magnetic active vertical suspension fitted to a service MkIII coach. Design of the actuators is described in the thesis along with the design of analogue and digital control systems. Two classical control systems were designed. a simple "Sky Hook" damper control system and a more sophisticated position control system developed from British Rail's experience with Maglev suspensions. A regulator designed using linear optimal control theory was found to give very good results in theory. However to implement the regulator it was necessary to design a system observer. In order to achieve a practically realisable observer considerable rationalisation of the vehicle model was required, which drew heavily on experience gained designing classical control systems. The classical control systems proved to be much easier to commission than the optimal controllers as they were designed with implementation in mind. During track testing problems of interaction between vehicles were encountered, as a result the biggest improvements in ride were obtained with the simple Sky Hook damper, as it was less specific to the vehicle than the other configurations. With further development one of the optimal control systems considered will probably turn out to be the most effective as it draws on the attributes of both classical and optimal design techniques.
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Muretto, Giovanni <1976>. "Design and control techniques of optical networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/403/1/Tesidott.pdf.
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The world of communication has changed quickly in the last decade resulting in the the rapid increase in the pace of peoples’ lives. This is due to the explosion of mobile communication and the internet which has now reached all levels of society. With such pressure for access to communication there is increased demand for bandwidth. Photonic technology is the right solution for high speed networks that have to supply wide bandwidth to new communication service providers. In particular this Ph.D. dissertation deals with DWDM optical packet-switched networks. The issue introduces a huge quantity of problems from physical layer up to transport layer. Here this subject is tackled from the network level perspective. The long term solution represented by optical packet switching has been fully explored in this years together with the Network Research Group at the department of Electronics, Computer Science and System of the University of Bologna. Some national as well as international projects supported this research like the Network of Excellence (NoE) e-Photon/ONe, funded by the European Commission in the Sixth Framework Programme and INTREPIDO project (End-to-end Traffic Engineering and Protection for IP over DWDM Optical Networks) funded by the Italian Ministry of Education, University and Scientific Research. Optical packet switching for DWDM networks is studied at single node level as well as at network level. In particular the techniques discussed are thought to be implemented for a long-haul transport network
that connects local and metropolitan networks around the world. The main issues faced are contention resolution in a asynchronous variable packet length environment, adaptive routing, wavelength conversion and node architecture. Characteristics that a network must assure as quality of service and resilience are also explored at both node and network level. Results are mainly evaluated via simulation and through analysis.
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Muretto, Giovanni <1976>. "Design and control techniques of optical networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/403/.
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The world of communication has changed quickly in the last decade resulting in the the rapid increase in the pace of peoples’ lives. This is due to the explosion of mobile communication and the internet which has now reached all levels of society. With such pressure for access to communication there is increased demand for bandwidth. Photonic technology is the right solution for high speed networks that have to supply wide bandwidth to new communication service providers. In particular this Ph.D. dissertation deals with DWDM optical packet-switched networks. The issue introduces a huge quantity of problems from physical layer up to transport layer. Here this subject is tackled from the network level perspective. The long term solution represented by optical packet switching has been fully explored in this years together with the Network Research Group at the department of Electronics, Computer Science and System of the University of Bologna. Some national as well as international projects supported this research like the Network of Excellence (NoE) e-Photon/ONe, funded by the European Commission in the Sixth Framework Programme and INTREPIDO project (End-to-end Traffic Engineering and Protection for IP over DWDM Optical Networks) funded by the Italian Ministry of Education, University and Scientific Research. Optical packet switching for DWDM networks is studied at single node level as well as at network level. In particular the techniques discussed are thought to be implemented for a long-haul transport network
that connects local and metropolitan networks around the world. The main issues faced are contention resolution in a asynchronous variable packet length environment, adaptive routing, wavelength conversion and node architecture. Characteristics that a network must assure as quality of service and resilience are also explored at both node and network level. Results are mainly evaluated via simulation and through analysis.
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Manzano, Ramos Edgar André. "Optimal control algorithm design for a prototype of active noise control system." Master's thesis, Pontificia Universidad Católica del Perú, 2017. http://tesis.pucp.edu.pe/repositorio/handle/123456789/8499.
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High-level noise can represent a serious risk for the health, industrial operations often
represent continuous exposure to noise, thus an important trouble to handle.
An alternative of solution can be the use of passive mechanisms of noise reductions,
nonetheless its application cannot diminish low-frequency noise.
Active Noise Control (ANC) is the solution used for low-frequency noise, ANC systems
work according to the superposition principle generating a secondary anti-noise
signal to reduce both.
Nevertheless, the generation of an anti-noise signal with same oppose characteristics
of the original noise signal presupposes the utilization of special techniques such
as adaptive algorithms. These algorithms involve computational costs.
The present research present the optimization of a specific ANC algorithm in the
step-size criteria. Delayed Filtered-x LMS (FxLMS) algorithm using an optimal
step-size is evaluated in a prototype of ANC system.Tesis
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Hicks, Dawn L. "Optimal design of digital model-following systems." Thesis, University of Salford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284423.
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Song, Yang. "Design of secondary voltage and stability controls with multiple control objectives." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29714.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.Committee Chair: Begovic, Miroslav; Committee Member: Deng, Shijie; Committee Member: Divan, Deepakraj; Committee Member: Harley, Ronald; Committee Member: Lambert, Frank; Committee Member: Shamma, Jeff. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Templeton, Brian Andrew. "A Polynomial Chaos Approach to Control Design." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28840.
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A method utilizing H2 control concepts and the numerical method of Polynomial Chaos was developed in order to create a novel robust probabilistically optimal control approach. This method was created for the practical reason that uncertainty in parameters tends to be inherent in system models. As such, the development of new methods utilizing probability density functions (PDFs) was desired.
From a more theoretical viewpoint, the utilization of Polynomial Chaos for studying and designing control systems has not been very thoroughly investigated. The current work looks at expanding the H2 and related Linear Quadratic Regulator (LQR) control problems for systems with parametric uncertainty. This allows solving deterministic linear equations that represent probabilistic linear differential equations. The application of common LTI (Linear Time Invariant) tools to these expanded systems are theoretically justified and investigated. Examples demonstrating the utilized optimization process for minimizing the H2 norm and parallels to LQR design are presented.
The dissertation begins with a thorough background section that reviews necessary probability theory. Also, the connection between Polynomial Chaos and dynamic systems is explained. Next, an overview of related control methods, as well as an in-depth review of current Polynomial Chaos literature is given. Following, formal analysis, related to the use of Polynomial Chaos, is provided. This lays the ground for the general method of control design using Polynomial Chaos and H2. Then an experimental section is included that demonstrates controller synthesis for a constructed probabilistic system. The experimental results lend support to the method.Ph. D.
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Tanil, Cagatay. "Optimal External Configuration Design Of Missiles." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610873/index.pdf.
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The main area of emphasis in this study is to investigate the methods and technology for aerodynamic configuration sizing of missiles and to develop a software platform in MATLAB®environment as a design tool which has an ability of optimizing the external configuration of missiles for a set of flight requirements specified by the user through a graphical user interface. A genetic algorithm based optimization tool is prepared by MATLAB is expected to help the designer to find out the best external geometry candidates in the conceptual design stage. Missile DATCOM software package is employed to predict the aerodynamic coefficients needed in finding the performance merits of a missile for each external geometry candidate by integrating its dynamic equations of motion. Numerous external geometry candidates are rapidly eliminated according to objectives and constraints specified by designers, which provide necessary information in preliminary design. In this elimination, the external geometry candidates are graded according to their flight performances in order to discover an optimum solution. In the conceptual design, the most important performance objectives related to the external geometry of a missile are range, speed, maneuverability, and control effectiveness. These objectives are directly related to the equations of motion of the missile, concluding that the speed and flight range are related to the total mass and the drag-to-lift ratio acting on missile. Also, maneuverability depends on the normal force acting on missile body and mass whereas the control effectiveness is affected by pitching moment and mass moment of inertia of missile. All of the flight performance data are obtained by running a two degree-of-freedom simulation. In order to solve the resulting multi-objective optimization problem with a set of constraint of linear and nonlinear nature and in equality and inequality forms, genetic-algorithm-based methods are applied. Hybrid encoding methods in which the integer configuration variables (i.e., nose shape and control type) and real-valued geometrical dimension (i.e., diameter, length) parameters are encoded in the same individual chromosome. An external configuration design tool (EXCON) is developed as a synthesis and external sizing tool for the subsonic cruise missiles. A graphical user interface (GUI), a flight simulator and optimization modules are embedded into the tool. A numerical example, the re-configuration problem of an anti-ship cruise missile Harpoon, is presented to demonstrate the accuracy and feasibility of the conceptual design tool. The optimum external geometries found for different penalty weights of penalty terms in the cost function are compared according to their constraint violations and launch mass values. By means of using EXCON, the launch mass original baseline Harpoon is reduced by approximately 30% without deteriorating the other flight performance characteristics of the original Harpoon.
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Foo, Yung Kuan. "Robustness of multivariable feedback systems : analysis and optimal design." Thesis, University of Oxford, 1985. http://ora.ox.ac.uk/objects/uuid:b0232383-ed71-42f1-92bc-597cd72c872b.
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The robustness of the stability property of multivariable feedback control systems with respect to model uncertainty is studied and discussed. By introducing a topological notion of arcwise connectivity, existing and new robust stability tests are combined and unified under a common framework. The new switching-type robust stability test is easy to apply, and does not require the nominal and perturbed plants to share the same number of closed right half-plane poles, or zeros, or both. It also highlights the importance of both the sensitivity matrix and the complementary sensitivity matrix in determining the robust stability of a feedback system. More specifically, it is shown that at those frequencies where there is a possibility of an uncertain pole crossing the jw-axis, robust stability is "maximized" by minimizing the maximum singular value of the sensitivity matrix. At frequencies where there is a likelihood of uncertain zeros crossing the imaginary axis, it is then desirable to minimize the maximum singular value of the complementary sensitivity matrix. A robustness optimization problem is posed as a non-square H∞-optimization problem. All solutions to the optimization problem are derived, and parameterized by the solutions to an "equivalent" two-parameter interpolation problem. Motivated by improvements in disturbance rejection and robust stability, additional optimization objectives are introduced to arrive at the 'best' solution.
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Wahl, Eric J. "The effect of damping on an optimally tuned dwell-rise-dwell cam designed by linear quadratic optimal control theory." Ohio : Ohio University, 1993. http://www.ohiolink.edu/etd/view.cgi?ohiou1176312992.
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André, Marine Charlotte. "Implications of adaptive learning for the design of optimal monetary policy." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAB004.
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La thèse étudie les implications des anticipations des agents privés formées avec l’apprentissage adaptatif pour la politique monétaire optimale dans des modèles Nouveau Keynésien. Les résultats obtenus sont comparés avec la littérature adoptant l’hypothèse d’anticipations rationnelles. La banque centrale fait l’arbitrage intertemporel introduit par les anticipations à apprentissage adaptatif entre stabiliser l’inflation maintenant et dans le futur. La distorsion générée par ces anticipations rend la politique monétaire davantage agressive, même si la présence du marché financier diminue légèrement l’agressivité de la politique monétaire. Il est optimal pour le gouvernement de choisir un banquier central libéral, ce résultat peut être mitigé par un contrat d’inflation linéaire. Un autre résultat est qu’il est optimal pour la banque centrale d’être moins indépendante en termes d’instruments par rapport aux anticipations rationnelles. La possibilité de contrôle robuste de la politique monétaire est limitée par l’apprentissage adaptatif en économie fermée, et encore plus limitée en économie ouverte. Mes travaux de recherche donnent des recommandations nouvellesThe dissertation studies the implications of private agents expectations formed with adaptive learning for the optimal monetary policy using New Keynesian models. The obtained results are compared with the literature adopting the hypothesis of rational expectations. The central bank makes the intertemporal trade-off between stabilizing current inflation or the future one that is introduced by adaptive learning expectations. The distortion which is introduced by this latter makes the monetary policy more aggressive, even if the presence of financial market slightly reduces the aggressiveness of the monetary policy. It is optimal for the government to choose a liberal central banker, but this result may be mitigated by adopting a linear inflation contract. Another result is that it is optimal for the central bank to be less instrument-independent compared to rational expectations. The possibility of robust control for monetary policy is limited by adaptive learning in a closed economy, and even more limited in an open economy. My research works give new recommendations for policy making
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Bohorquez, dorante Nestor. "Design of safe control laws for the locomotion of biped robots." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT110/document.
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Un robot bipède doit pouvoir marcher en toute sécurité dans une foule. Pour cela, il faut prendre en compte deux aspects : l’équilibre et l'évitement des collisions. Maintenir l’équilibre implique d'éviter les défaillances dynamiques et cinématiques de la dynamique instable du robot. Pour ce qui est de l’évitement des collisions, il s’agit d’éviter le contact entre le robot et des individus. Nous voulons être capables de satisfaire ces deux contraintes simultanément, à l’instant présent mais aussi dans le futur. Nous pouvons assurer l’équilibre du robot indéfiniment en le faisant entrer dans un cycle limite de marche ou en le faisant s’arrêter après quelques pas. Néanmoins, une telle garantie pour l’évitement d’obstacle n’est pas possible pour plusieurs raisons : impossibilité de connaître de manière absolue la direction vers laquelle les individus se dirigent, limitations cinématiques et dynamiques du robot, mouvement adverse de la foule, etc. Nous traitons ces limitations avec une stratégie standard de navigation dans une foule, appelée passive safety, qui nous permet de formuler une loi de commande prédictive avec laquelle nous assurons l’équilibre et l'évitement des collisions, de manière unifiée, en faisant s’arrêter le robot de manière sécurisée et en temps fini. De plus, nous définissons une nouvelle stratégie de navigation sûre basée sur le principe d’évitement des collisions aussi longtemps que possible, qui a la propriété de minimiser leur apparition et sévérité. Nous proposons une formulation lexicographique qui synthétise des mouvements conformes à ce principe. Nous augmentons les degrés de liberté de la locomotion d’un robot bipède en permettant la variation de l’orientation et de la durée des pas en ligne. Cependant, cela introduit des non-linéarités dans les contraintes de nos problèmes d’optimisation. Nous faisons des approximations de ces contraintes non-linéaires avec des contraintes linéaires sûres de sorte que la satisfaction des secondes implique la satisfaction des premières. Nous proposons une nouvelle méthode de résolution des problèmes non-linéaires (Optimisation Quadratique Successive Sûre) qui assure la faisabilité des itérations de Newton en utilisant cette redéfinition des contraintes. Nous simulons la marche d’un robot bipède dans une foule pour évaluer la performance de nos lois des commandes. D’une part, nous réussissons à réduire (statistiquement) la quantité et la sévérité des collisions en comparaison avec la méthode de passive safety, spécialement dans les conditions d’incertitude de la marche du robot dans une foule. D’autre part, nous montrons des exemples de comportements typiques du robot, qui découlent de la liberté de choisir l’orientation et la durée des pas. Nous rapportons le coût de calcul de notre méthode de résolution des problèmes non-linéaires en comparaison avec une méthode standard. Nous montrons qu’une seule itération de Newton est nécessaire pour arriver à une solution faisable, mais que le coût de calcul dépend du nombre de factorisations de l’active set dont nous avons besoin pour arriver à l’active set optimalWe want a biped robot to walk safely in a crowd. This involves two aspects: balance and collision avoidance. The first implies avoiding kinematic and dynamical failures of the unstable walking dynamics of the robot; the second refers to avoiding collisions with people. We want to be able to solve both problems not only now but also in the future. We can ensure balance indefinitely by entering in a cyclic walk or by making the robot stop after a couple of steps. Nonetheless, we cannot give a comparable guarantee in collision avoidance for many reasons: impossibility of having absolute knowledge of where people are moving, kinematic/dynamical limitations of the robot, adversarial crowd motion, etc. We address this limitation with a standard strategy for crowd navigation, known as passive safety, that allows us to formulate a unified Model Predictive Control approach for balance and collision avoidance in which we require the robot to stop safely in finite time. In addition, we define a novel safe navigation strategy based on the premise of avoiding collisions for as long as possible that minimizes their occurrence and severity. We propose a lexicographic formulation that produces motions that comply with such premise.We increase the degrees of freedom of the locomotion of a biped robot by allowing the duration and orientation of its steps to vary online. This introduces nonlinearities in the constraints of the optimization problems we solve. We approximate these nonlinear constraints with safe linear constraints so that satisfying the latter implies satisfying the former. We propose a novel method (Safe Sequential Quadratic Programming) that ensures feasible Newton iterates in the solution of nonlinear problems based on this redefinition of constraints.We make a series of simulations of a biped robot walking in a crowd to evaluate the performance of our proposed controllers. We are able to attest the reduction in the number and in the severity of collisions with our proposed navigation strategy in comparison with passive safety, specially when there is uncertainty in the motion of people. We show typical behaviors of the robot that arise when we allow the online variation of the duration and orientation of the steps and how it further improves collision avoidance. We report the computational cost of our proposed numerical method for nonlinear problems in comparison with a standard method. We show that we only need one Newton iteration to arrive to a feasible solution but that the CPU time is dependent on the amount of active set factorizations needed to arrive to the optimal active set
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Pokrud, Boonyarit. "H∞ optimal control : general solution by interpolation and design with multiple objective functions." Thesis, University of Surrey, 1989. http://epubs.surrey.ac.uk/847911/.
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A new method for solving Hinfinity control problems is developed. The method makes use of the Youla parametrization to characterize the set of all stabilizing controllers K(s) in terms of a stable function Q(s). and also to transform the Hinfinity control problem into a model-matching problem with an objective function E(s) being linear in Q(s). The model-matching problem is then solved by using the interpolation results of Hung. In the general case (i.e. problems of the 3rd kind) closed-form state-space characterizations of optimal and suboptimal solutions for Q(s) and E(s) are given. Furthermore, the solutions generally only require to solve two standard algebraic Riccati equations of smaller size than the McMillan degree of the (generalized) plant. This has an advantage of alleviating the computation burden associated with the ?-iteration required for determining the attainable minimum of ||E(s)||[infinity]. The Hinfinity approach to feedback design with multiple objective functions is studied in this thesis. For a system with two objective functions T[i](s), (i = 1, 2) a design criterion of minimizing the function max (||T[1](s)||[infinity], ||T[2](s)||[infinity]) subject to internal stability of the closed-loop system is proposed. The problem is formulated as an Hinfinity control problem and an iterative algorithm for obtaining a solution is given. A numerical example is given to illustrate the effectiveness of the proposed design technique for tightly bounding and shaping the frequency responses of two objective functions. The application of Hinfinity feedback design techniques to the control of flexible structures is investigated. Experiments are conducted in order to evaluate the use of the Hinfinity approach to the control of flexible structures. An Hinfinity optimal controller is designed and implemented in a laboratory system to manoeuvre a cantilever flexible beam and simultaneously control its vibrations. The controller performance is then assessed. The results obtained are shown to be satisfactory and encouraging.
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Benner, Peter, and Jens Saak. "Linear-Quadratic Regulator Design for Optimal Cooling of Steel Profiles." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200601597.
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We present a linear-quadratic regulator (LQR) design for a heat transfer model describing the cooling process of steel profiles in a rolling mill. Primarily we consider a feedback control approach for a linearization of the nonlinear model given there, but we will also present first ideas how to use local (in time) linearizations to treat the nonlinear equation with a regulator approach. Numerical results based on a spatial finite element discretization and a numerical algorithm for solving large-scale algebraic Riccati equations are presented both for the linear and nonlinear models.
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Zhang, Xuan. "Scalable (re)design frameworks for optimal, distributed control in power networks." Thesis, University of Oxford, 2015. http://ora.ox.ac.uk/objects/uuid:4121ae7d-d505-4d3d-8ea6-49efeb9ba048.
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In this thesis, we develop scalable frameworks to (re)design a class of large-scale network systems with built-in control mechanisms, including electric power systems and the Internet, in order to improve their economic efficiency and performance while guaranteeing their stability and robustness. After a detailed introduction relating to power system control and optimization, as well as network congestion control, we turn our attention to merging primary and secondary frequency control for the power grid. We present modifications in the conventional generation control using a consensus design approach while considering the participation of controllable loads. The optimality, stability and delay robustness of the redesigned system are studied. Moreover, we extend the proposed control scheme to (i) networks with more complexity and (ii) the case where controllable loads are involved in the optimization. As a result, our controllers can balance power flow and drive the system to an economically optimal operating point in the steady state. We then study a real-time control framework that merges primary, secondary and tertiary frequency control in power systems. In particular, we consider a transmission level network with tree topology. A distributed dynamic feedback controller is designed via a primal-dual decomposition approach and the stability of the overall system is studied. In addition, we introduce extra dynamics to improve system performance and emphasize the trade-off when choosing the gains of the extra dynamics. As a result, the proposed controller can balance supply and demand in the presence of disturbances, and achieve optimal power flow in the steady state. Furthermore, after introducing the extra dynamics, the transient performance of the system significantly improves. A redesign framework for network congestion control is developed next. Motivated by the augmented Lagrangian method, we introduce extra terms to the Lagrangian, which is used to redesign the primal-dual, primal and dual algorithms. We investigate how the gains resulting from the extra dynamics influence the stability and robustness of the system. Moreover, we show that the overall system can achieve added robustness to communication delays by appropriately tuning these gains. Also, the meaning of these extra dynamics is investigated and a distributed proportional-integral-derivative controller for solving network congestion control problems is further developed. Finally, we concentrate on a reverse- and forward-engineering framework for distributed control of a class of linear network systems to achieve optimal steady-state performance. As a typical illustration, we use the proposed framework to solve the real-time economic dispatch problem in the power grid. On the other hand, we provide a general procedure to modify control schemes for a special class of dynamic systems. In order to investigate how general the reverse- and forward-engineering framework is, we develop necessary and sufficient conditions under which an linear time-invariant system can be reverse-engineered as a gradient algorithm to solve an optimization problem. These conditions are characterized using properties of system matrices and relevant linear matrix inequalities. We conclude this thesis with an account for future research.
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Merkoulova, Daniel. "Optimal Input Design by Model Predictive Control for System Identification." Thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215712.
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Mathematical models are an essential part of analysis of autonomous systemsas they ease the formulation of control laws and allow experiments tobe performed in a simulation environment. For complex systems, parts of themodel may be missing which increases uncertainties and limits practical applications.Using input-output measurements makes it possible to estimate themodel, but requires the measurements to be informative. The idea in so-calledinput design is to find an input sequence for the system such that the measurementsreveal the properties and dynamics of the true system as much aspossible. This is commonly formulated as an optimization problem.This thesis focuses on formulating an optimization algorithm for inputdesign, which is implemented as an open-loop receding horizon optimizationproblem. The problem consists of classical A-, D-, E-optimality criteria andfinite combinatorial constraints on the input signal. The resulting optimizationproblem is non-convex. Two approaches are explored to solve the problem;a combinatorial and a convex relaxation. The method is finally evaluated ina simulation environment on a second-order system and first-order linearizedwater tank system.Matematiska modeller är essentiella när det kommer till autonoma systemeftersom det förenklar formuleringar av styrlagar och tillåter tester i simuleringsmiljöer.För komplexa system kan delar av modellen saknas vilket ökarosäkerheten hos modellen och begränsar praktiska tillämpningar. Genom attanvända in-ut data är det möjligt att estimera modellen men det kräver attmätningarna är av relativ kvalitet. Idén är således att finna en sekvens av indataså att dynamiken hos systemet avslöjas vilket kan formuleras som ettoptimeringsproblem.Det här arbetet fokuserar på att formulera ett optimeringsproblem somska implementeras i modell prediktiv reglering. Problemet består utav klassiskA,D, E-optimalitet med begränsade diskreta bivillkor på insignalen. Metodenevalueras i simulering på ett godtyckligt andra ordningens system och på ettlineariserat första ordningens vattentankssystem.
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Seifried, Robert [Verfasser]. "Dynamics of Underactuated Multibody Systems : Modeling, Control and Optimal Design." Dordrecht : Springer Netherlands, 2014. http://d-nb.info/1044031832/34.
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Bergkvist, Joel. "Optimal Design of Network for Control of Total Station Instruments." Thesis, KTH, Geodesi och satellitpositionering, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172426.
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This thesis uses the Minimum Norm Quadratic Unbiased Estimation (MINQUE) to estimatestandard deviation of observations of a total station. Different setups are created byaltering the number of stations and targets and their relative position in the network tostudy the effect that different setups have to the estimation and define what are importantto minimize the effect of the setup to the estimation.A lot of research has been done around methods for estimation of variance and covariancecomponents, since it is useful in many fields. Various approaches exists to solve theproblem of variance components estimation. Geodesy is a special case, were their often isa apriori knowledge of how well an instrument is able to record measurements. There isan ISO-standard for testing and verification of geodetic instrument but also an alternativeapproach the KTH-Total Station Check.For the estimation three main types of setups were defined and used in the simulation.These main types were then altered to see how different changes to the setup effect theoverall estimation. The alterations were changes in distance between station and targets,changes in vertical distance between stations and targets and the amount of observationscarried out by adding more stations and targets to the setups.The result of the simulations shows that the tested changes in the setups do effectthe estimation. It was not possible to determine by how much for each change, becausea change in vertical displacement also meant a change in angles and distance betweenthe station and the target. Increasing the amount of stations and targets or one of themshows that standard deviation of the estimation becomes smaller. The effect can be seenindependent of which type of setup that is used. The most important factor to how goodthe estimation will be is the amount of observations.
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Majecki, Pawel. "Polynomial approach to optimal control design, tuning and performance assessment." Thesis, University of Strathclyde, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.501854.
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MANZOCCHI, Diego. "Hierarchical supervisory optimal control design approach for industrial sustainable systems." Doctoral thesis, Università degli studi di Bergamo, 2015. http://hdl.handle.net/10446/33697.
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The production landscape is changing. Traditionally, the energy costs represented a small part of the production expenses, meaning that the design of production facilities usually neglected investments in efficient energy usage in favour of more important factors, such as the maximization of production throughput; the energy consumption of factories has been in fact always high, but the cost of energy has increased dramatically in the last decades, pushing the industrial representatives to search for higher level of efficiency. This scenario, however, is changing rapidly. According to the International Energy Agency, manufacturing is responsible for approximately 37% of global primary energy consumption being the largest energy consumer and CO2 producer. Improvement of energy/resource efficiency is the key to reduce environmental impact and is mentioned as driver to reach European 20/20/20 goals. In order to obtain an efficient work and material flow, and achieve such challenging results, an overall optimization of the whole concept of Factory has to be pursued, introducing a new holistic vision of the production environment, with comprehensive interventions acting both at methodological and technological level. During the last decades, pushed by eco-oriented policies and standards, the European manufacturing industries has seen a clear path of introduction of new technologies within the production environment (or on its boundaries) conceived to reduce energy consumption, recycle wastes or filter emissions. However, in the majority of those cases, “production is still the king” and these systems are regarded mainly as a support function whose objective is to provide additional services to the production unit. Within this situation, in spite of the fact that the activity level of these add-in systems is dependent on the production management of the main process, the energy, waste and emissions considerations are rarely included during design phase or in the planning, scheduling and control procedures. Recently, new technologies have done important steps regarding energy efficiency in terms of mechanisms, actuators and sensors. Complementary to this improvements at component level, considerable savings, with minor efforts for a factory, can also be obtained by introducing new adaptive control architectures, as supervisory optimizers of the pre-existing controllers, able to predict the evolution of the system and consequently modify its current behaviour in order to achieve the same production results but with less energy consumed (remark: energy is considered as the main performance criterion to be optimized, but the techniques are clearly independent from that effectively selected).
The main techniques studied and successfully applied in real-case scenarios to perform the adaptive control of a process are usually grouped under the Model Predictive Control (MPC) family, but their implementation in complex, non-linear industrial environments is still limited, and requires the development of ad-hoc engineered solutions. Different implementation of MPC can be found in a wide variety of industrial application areas, including chemicals, food processing, automotive and aerospace with better results than classical control approaches such as a cascade control. Especially, in Iron&Steel industry, can be find application of MPC techniques in the Continuous Emission Monitoring Systems (CEMS or PEMS) (i.e. Pavilion8 by Rockwell-Automation) but almost nothing, for instance, in the Energy Management System (EMS), and in the control of furnaces and related equipment, that represent the most energy intensive elements with respect to the rest of the plant.
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Wong, David Ka-Kui. "The synthesis of linear-optimal heave control of electromagnetic suspension systems." Thesis, University of Bath, 1985. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370456.
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This thesis is concerned with the synthesis of linear-optimal heave control of electromagnetic suspension systems. The methods of computer-aided analysis and simulation were employed in this research. The intrinsic properties of electromagnetic suspension system were investigated to facilitate the synthesis and to provide guidelines for the design of electromagnets or linear motors suitable for use in suspension systems. The technique of complementary filtering, which resolves the conflicting requirements of high stiffness to load and high compliance for ride-comfort, was further developed. This led to the ability of directly comparing the merits of systems with different configurations and determining the optimal natural frequency. Together with a novel way of removing steady state gap error during the traversing of transition curves, the filtering technique was applied to the system using fixed-gain and sliding-mode variable-structure control methods. The latter method is well known for its abi1ity in maintaining closed-loop characteristics in the presence of disturbance. However, further development was required before it was applied. The resultant suspension system gave a 20% improvement in ride-quality over the best published result which was carried out under similar test conditions. Even so, theoretical analysis showed that a four-fold improvement may be possible.
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Chin, Chang-Ho. "Optimal filter design approaches to statistical process control for autocorrelated processes." Texas A&M University, 2004. http://hdl.handle.net/1969.1/2776.
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Statistical Process Control (SPC), and in particular control charting, is widely used to achieve and maintain control of various processes in manufacturing. A control chart is a graphical display that plots quality characteristics versus the sample number or the time line. Interest in effective implementation of control charts for autocorrelated processes has increased in recent years. However, because of the complexities involved, few systematic design approaches have thus far been developed.
Many control charting methods can be viewed as the charting of the output of a linear filter applied to the process data. In this dissertation, we generalize the concept of linear filters for control charts and propose new control charting schemes, the general linear filter (GLF) and the 2nd-order linear filter, based on the generalization. In addition, their optimal design methodologies are developed, where the filter parameters are optimally selected to minimize the out-of-control Average Run Length (ARL) while constraining the in-control ARL to some desired value. The optimal linear filters are compared with other methods in terms of ARL performance, and a number of their interesting characteristics are discussed for various types of mean shifts (step, spike, sinusoidal) and various ARMA process models (i.i.d., AR(1), ARMA(1,1)).
Also, in this work, a new discretization approach for substantially reducing the computational time and memory use for the Markov chain method of calculating the ARL is proposed. Finally, a gradient-based optimization strategy for searching optimal linear filters is illustrated.
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Safi, Samghabadi Pedram. "Kinematic analysis and control design of a retractable wheel mechanism using optimal control theory." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1527340.
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Mobile robots are un-manned systems and must be able to overcome the obstacles they face without human intervention. In this research we have proposed a novel retractable mechanism which converts a linear hydraulic motion into expansion of six claws at each wheel. In order to control the expansion, optimal control theory was applied and a constrained optimization problem was defined using different Simulink toolboxes and applied to the mechanism modeled in SimHydraulics/SimMechanics. The main benefit of performing both hydraulic and mechanical system simulation and also control design in the same environment is to eliminate mathematical approximation of the model and using existing Simulink simulation tools for simulation and control. Systems were modeled and controller optimization was performed. Simulation results are illustrated at the end, which show the method's versatility and reliability for controlling the mechanism operation.
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Androulakakis, Pavlos. "Evolutionary Design of Near-Optimal Controllers for Autonomous Systems Operating in Adversarial Environments." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627665780943046.
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Chayopitak, Nattapon. "Performance Assessment and Design Optimization of Linear Synchronous Motors for Manufacturing Applications." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16281.
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The major contributions of this thesis are categorized into three areas: (i) magnetic modeling, (ii) optimal performance assessment and (iii) multi-objective design methodology of the linear permanent-magnet (LPM) and linear variable reluctance (LVR) motors for manufacturing automation applications. The target application is to perform repetitive point-to-point positioning tasks on a continuous basis under temperature constraints. Through simplification, the constraint on temperature rise may be replaced by a constraint on average power dissipation, provided that the thermal resistance is constant and known.
The basic framework of analysis is first introduced for a class of idealized linear synchronous (LS) motors, where magnetic saturation and spatial harmonics are neglected, to provide clarity and insight. The physics-based force models for the LPM and LVR motors, including spatial harmonics and magnetic saturation as appropriate, are then developed. Due to magnetic linearity, the force model of the LPM motor is derived from the analytical solution of the Poisson Equation. A nonlinear magnetic circuit analysis model is developed for the LVR motor that includes both spatial harmonics and magnetic saturation. The accuracy of both force models are verified by finite element analysis.
Applying those force models, the optimal performance assessment of the LPM and LVR motors is explored using the mathematical framework discussed for the idealized LS motors. In particular, the relationship between travel time and travel distance is characterized in terms of average power dissipation. The performance assessment methodologies developed here may be applied to any motor technology used in manufacturing automation applications.
The multi-objective design optimization problem is then defined and software for its solution is developed using Monte-Carlo synthesis, the performance assessment tools and dominance-based sorting. Design results for the LPM and LVR motors are then presented. Future research is discussed as the conclusion of the thesis.
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Kadlec, Ronald James 1960. "Design of a digital tracking control system for optical disk drive applications." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276564.
Full textAbstract:
A large spectrum of new technologies are being explored in the optical disk drive systems. Optics, lasers, media, and servomechanisms are a few examples. This thesis will be directed to the study of a servomechanism used in a majority of the optical disk drives, commonly referred to as the tracking servomechanism. The tracking servomechanism, consisting of a fine and a coarse actuator, is mechanically analyzed by the use of free body diagrams. A transfer function for each actuator is derived. Analog compensators are designed to achieve specific phase and gain margin requirements. A digital compensator is derived from the analog compensator by the use of a mapping technique. Major contributions of this thesis include studies to determine an acceptable sampling rate, number of bits, and computation delay associated with the implementation of a digital servo controller in a tracking servomechanism.