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Nguyen, Canh Quang Mechanical & Manufacturing Engineering Faculty of Engineering UNSW. „Switching robust adaptive control in nonlinear mechanical systems“. Awarded by:University of New South Wales. School of Mechanical & Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/24318.
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This work describes analysis, design, and implementation of a novel switching robust adaptive control (SRAC) method for nonlinear systems. The proposed method takes advantage of both adaptive control (AC) and robust control (RC) methods. SRAC employs one of the methods when this method is advantageous and switches to the other method when the other one becomes the preferred choice. To this end, RC is used to deal with transient effects caused by uncertainties and disturbances. The system switches over to AC for good steady state performance when certain switching criteria are satisfied. If external disturbances become dominant or new uncertainties are introduced while AC is active, the system will switch back to RC. In this manner, the switching process between AC and RC will continue to take place guaranteeing improved performance, robustness, and accuracy for the entire operation of the system. The novel idea behind the proposed method is a smart novel mechanism of bi-directional switching between RC and AC. In this mechanism, the involvement of estimators and switching rules play a decisive part in guaranteeing the smooth switching and the stability of the system. The implementation and design issues of the novel method were first evaluated by simulation on a mass spring system and then on a robot manipulator system. To control these systems with satisfactory performance, nonlinearities and uncertainties have been properly analysed and embedded into models and control algorithms. Simulation results showed the superior performance of the proposed method compared with other control methods. The experimental validation of the proposed method was conducted on a Puma 560 robot manipulator system which was established by joints 2 and 3 of the robot. Extensive comparative experimental results have validated the efficacy and superior performance of the proposed SRAC method over other control methods in the face of uncertainties and disturbances. As part of this work, a comprehensive dynamic model of robotic manipulator in the presence of joint motors, gravitational forces, friction forces and payload has been developed using MAPLE. A systematic design framework for the SRAC method has also been developed.
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Trebi-Ollennu, Ashitey. „Robust nonlinear control, designs using adaptive fuzzy systems“. Thesis, Cranfield University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296492.
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Lopez, Brett Thomas. „Adaptive robust model predictive control for nonlinear systems“. Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122395.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 115-124).
Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube centered around a desired nominal trajectory (generated online). While tube MPC regains tractability, there are several theoretical and practical problems that must be solved for it to be used in real-world scenarios. First, the decoupled trajectory and control design is inherently suboptimal, especially for systems with changing objectives or operating conditions. Second, no existing tube MPC framework is able to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. And third, the inability to reduce state-dependent uncertainty through online parameter adaptation/estimation leads to systematic error in the trajectory design. This thesis aims to address these limitations by developing a computationally tractable nonlinear tube MPC framework that is applicable to a broad class of nonlinear systems.
"This work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374, by the DARPA Fast Lightweight Autonomy (FLA) program, by the NASA Convergent Aeronautics Solutions project Design Environment for Novel Vertical Lift Vehicles (DELIVER), and by ARL DCIST under Cooperative Agreement Number W911NF- 17-2-0181"--Page 7.
by Brett T. Lopez.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Aeronautics and Astronautics
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Zhang, Zhen. „Adaptive robust periodic output regulation“. Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187118803.
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Fisher, James Robert. „Aircraft control using nonlinear dynamic inversion in conjunction with adaptive robust control“. Texas A&M University, 2004. http://hdl.handle.net/1969.1/1515.
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This thesis describes the implementation of Yaos adaptive robust control to an aircraft
control system. This control law is implemented as a means to maintain stability and tracking
performance of the aircraft in the face of failures and changing aerodynamic response.
The control methodology is implemented as an outer loop controller to an aircraft under
nonlinear dynamic inversion control.
The adaptive robust control methodology combines the robustness of sliding mode
control to all types of uncertainty with the ability of adaptive control to remove steady state
errors. A performance measure is developed in to reflect more subjective qualities a pilot
would look for while flying an aircraft. Using this measure, comparisons of the adaptive
robust control technique with the sliding mode and adaptive control methodologies are
made for various failure conditions. Each control methodology is implemented on a full
envelope, high fidelity simulation of the F-15 IFCS aircraft as well as on a lower fidelity full
envelope F-5A simulation. Adaptive robust control is found to exhibit the best performance
in terms of the introduced measure for several different failure types and amplitudes.
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Muenst, Gerhard. „Mass movement mechanism for nonlinear, robust and adaptive control of flexible structures“. Ohio : Ohio University, 2001. http://www.ohiolink.edu/etd/view.cgi?ohiou1174061987.
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Poon, Kai-yin Kenny. „An investigation on the application of nonlinear robust adaptive control theory in AC/DC power systems“. Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38898949.
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Hayakawa, Tomohisa. „Direct Adaptive Control for Nonlinear Uncertain Dynamical Systems“. Diss., Georgia Institute of Technology, 2003. http://hdl.handle.net/1853/5292.
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In light of the complex and highly uncertain nature of dynamical systems
requiring controls, it is not surprising that reliable system models for many
high performance engineering and life science applications are unavailable. In
the face of such high levels of system uncertainty, robust controllers may
unnecessarily sacrifice system performance whereas adaptive controllers are
clearly appropriate since they can tolerate far greater system uncertainty
levels to improve system performance. In this dissertation, we develop a
Lyapunov-based direct adaptive and neural adaptive control framework that
addresses parametric uncertainty, unstructured uncertainty, disturbance
rejection, amplitude and rate saturation constraints, and digital
implementation issues. Specifically, we consider the following research topics:
direct adaptive control for nonlinear uncertain systems with exogenous
disturbances; robust adaptive control for nonlinear uncertain systems; adaptive
control for nonlinear uncertain systems with actuator amplitude and rate
saturation constraints; adaptive reduced-order dynamic compensation for
nonlinear uncertain systems; direct adaptive control for nonlinear matrix
second-order dynamical systems with state-dependent uncertainty; adaptive
control for nonnegative and compartmental dynamical systems with applications
to general anesthesia; direct adaptive control of nonnegative and compartmental
dynamical systems with time delay; adaptive control for nonlinear nonnegative
and compartmental dynamical systems with applications to clinical pharmacology;
neural network adaptive control for nonlinear nonnegative dynamical systems;
passivity-based neural network adaptive output feedback control for nonlinear
nonnegative dynamical systems; neural network adaptive dynamic output feedback
control for nonlinear nonnegative systems using tapped delay memory units;
Lyapunov-based adaptive control framework for discrete-time nonlinear systems
with exogenous disturbances; direct discrete-time adaptive control with
guaranteed parameter error convergence; and hybrid adaptive control for
nonlinear uncertain impulsive dynamical systems.
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Patre, Parag. „Lyapunov-based robust and adaptive control of nonlinear systems using a novel feedback structure“. [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024807.
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Poon, Kai-yin Kenny, und 潘啟然. „An investigation on the application of nonlinear robust adaptive control theory in AC/DC power systems“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38898949.
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Zeng, Chao. „Develop a robust nonlinear controller for large aircraft by applying NDI, SMC and adaptive control“. Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/7949.
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A nonlinear dynamic inversion (NDI) controller and a sliding mode controller are
developed for large civil transport Boeing 747 in this thesis. Furthermore adaptive
control theory is applied on both NDI controller and SMC controller to improve the
performance. Nonlinear dynamic inversion is an advanced control method which
is able to directly handle nonlinear system with less gain schedule and provides
inherent decoupled property. The system is linearized as a pure integrator by inner
loop feedback, whilst the desired control law is fulfilled by the outer loop linear
controller. However, the NDI controller is considerably sensitive to uncertainty due
to the incomplete cancellation. SMC, a well known nonlinear robust control method,
is utilized to endow the controller with more robustness. The results show that SMC
controllers perform better than NDI controllers, but are still not perfect. Finally, a
parameter on-line estimation adaptive scheme is applied to improve NDI controller
meanwhile a disturbance observer is designed in addition to SMC controller. It is
drawn from assessments that the disturbance observer based SMC controller achieves
the best performance for all flight points: fast rising-up speed, little overshoot, short
settle time and very small steady state error.
In addition, the classical and modern linear control theories as well as nonlinear
control methods are reviewed. Moreover, some flying and handling quality criteria
are also given as literature review.
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Maalouf, Divine. „Contribution to nonlinear adaptive control of low inertia underwater robots“. Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20196/document.
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L'utilisation des véhicules sous-marins (ROV, AUV, gliders) s'est considérablement accrue ces dernières décennies, aussi bien dans le domaine de l'offshore ou de l'océanographie, que pour des applications militaires. Dans cette thèse, nous abordons le problème particulier de la commande des véhicules sous-marins à faible inertie et fort rapport puissance/inertie. Ces derniers constituent des systèmes fortement non linéaires, dont la dynamique est susceptible de varier au cours du temps (charge embarquée, caractéristiques des propulseurs, variation de salinité...) et qui sont très sensibles aux perturbations environnementales (chocs, traction sur l'ombilical...). Afin d'assurer des performances de suivi de trajectoire satisfaisantes, il est nécessaire d'avoir recours à une commande adaptative qui compense les incertitudes ou les variations des paramètres du modèle dynamique, mais également qui rejette les perturbations, telles que les chocs. A cette fin, nous proposons dans ce manuscrit, l'étude théorique et la validation expérimentale de plusieurs lois de commande pour véhicules sous-marins. Nous analysons tout d'abord des approches classiques dans ce domaine (commande PID et commande par retour d'état non linéaire), puis nous les comparons avec deux autres architectures de commande. La première est la commande adaptative L1 non linéaire, introduite en 2010 notamment pour la commande des véhicules aériens, et implémentée pour la première fois sur un véhicule sous-marin. Le découplage entre adaptation et robustesse permet l'utilisation de très grands gains d'adaptation (et donc une convergence plus rapide des paramètres estimés, sans aucune connaissance a priori), sans pour autant dégrader la stabilité. La seconde méthode, que nous proposons et qui constitue l'apport principal de cette thèse, est une évolution de la commande L1, permettant d'en améliorer les performances lors du suivi d'une trajectoire variable. Nous présentons une analyse de stabilité de cette commande, ainsi que sa comparaison expérimentale avec les autres lois de commande (commande PID, commande adaptative par retour d'état non linéaire et commande adaptative L1 standard). Ces expérimentations ont été réalisées sur un mini-ROV et plusieurs scenarii ont été étudiés, permettant ainsi d'évaluer, pour chaque loi, sa robustesse et son aptitude à rejeter les perturbationsUnderwater vehicles have gained an increased interest in the last decades given the multiple tasks they can accomplish in various fields, ranging from scientific to industrial and military applications. In this thesis, we are particularly interested in the category of vehicles having a high power to weight ratio. Different challenges in autonomous control of such highly unstable systems arise from the inherent nonlinearities and the time varyingbehavior of their dynamics. These challenges can be increased by the low inertia of this class of vehicles combined with their powerful actuation. A self tuning controller is therefore required in order to avoid any performance degradation during a specific mission. The closed-loop system is expected to compensate for different kinds of disturbances or changes in the model parameters. To solve this problem, we propose in this work the design,analysis and experimental validation of different control schemes on an underwater vehicle. Classical methods are initially proposed, namely the PID controller and the nonlinear adaptive state feedback (NASF) one, followed by two more advanced schemes based on the recently developed L1 adaptive controller. This last method stands out among the other developed ones in its particular architecture where robustness and adaptation are decoupled. In this thesis, the original L1 adaptive controller has been designed and successfullyvalidated then an extended version of it is proposed in order to deal with the observed time lags occurring in presence of a varying reference trajectory. The stability of this latter controller is then analysed and real-time experimental results for different operating conditions are presented and discussed for each proposed controller, assessing their performance and robustness
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Andrecioli, Ricardo. „Grasped Object Detection for Adaptive Control of a Prosthetic Hand“. University of Akron / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779.
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Yan, Xinming. „Development of robust control based on sliding mode for nonlinear uncertain systems“. Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0012.
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Le travail de thèse présenté dans ce mémoire s’inscrit dans le cadre du développement de lois de commande pour des systèmes non linéaires incertains, basées sur la théorie des modes glissants. Les méthodes classiques de la commande par modes glissants sont des lois de commande par retour d’état, où la variable de glissement et ses dérivées sont nécessaires. Le premier objectif de cette thèse est de proposer des lois de commande par modes glissants d’ordre supérieur avec une réduction de l’ordre de dérivation de la variable de glissement. Le deuxième objectif est de combiner les nouvelles lois de commande avec un mécanisme de gain adaptatif. L’utilisation d’un gain adaptatif permet de simplifier le réglage du gain, de réduire le temps de convergence et d’améliorer la précision. Enfin, l’applicabilité de ces approches est démontrée à travers leur application au banc d’essais électropneumatique de l’IRCCyN, et à un système volant à trois degrés de libertéThis work deals with the development of control laws for nonlinear uncertain systems based onsliding mode theory. The standard sliding mode control approaches are state feedback ones, in which the sliding variable and its time derivatives are required. This first objective of this thesis is to propose high order sliding mode control laws with a reduced use of sliding variable time derivatives. The contributions are made for the second and third order sliding mode control. The second objective is to combine the proposed control laws with a gain adaptation mechanism. The use of adaptive gain law allows to simplify the tuning process, to reduce the convergence time and to improve the accuracy. Finally, the applicability of the proposed approaches is shown on IRCCyN pneumatic benchmark. Applications are also made on 3DOF flying system
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Zeng, Sheng. „Robust Adaptive Control Design for Classes of SISO and MIMO Linear Systems Under Noisy Output Measurements“. University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1172767648.
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LIUZZO, STEFANO. „Adaptive learning control of nonlinear systems with applications to robot manipulators“. Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2008. http://hdl.handle.net/2108/578.
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The goal of the proposed work is the design of adaptive learning controls for nonlinear systems with output dependent nonlinearities and for robot manipulators. At first, we address the problem of designing an output error feedback control for single input, single output nonlinear systems with uncertain, smooth, output dependent nonlinearities whose local Lipschitz constants are known. The considered systems are required to be observable, minimum phase with known relative degree and known high frequency gain sign: linear systems are included. The reference output signal is assumed to be smooth and periodic with known period. By developing in Fourier series expansion a suitable periodic input reference signal, an output error feedback adaptive learning control is designed which 'learns' the input reference signal by identifying its Fourier coefficients: bounded closed loop signals and exponential tracking of both input and output reference signals are obtained when the Fourier series expansion is finite, while arbitrary small tracking errors are exponentially achieved otherwise. The resulting control is not model based, is independent of the system order and depends only on the relative degree, the reference signal period and the high frequency gain sign. Then, the properties of the designed adaptive learning controllers are studied with reference to robotic manipulators. Global adaptive learning controls are designed for robotic manipulators with revolute joints and uncertain dynamics: state feedback and output feedback tracking controllers are designed. The reference signals to be tracked are assumed to be smooth and either constant or periodic with known period. Two adaptive learning controllers are designed which 'learn' the torque reference signals of each manipulator's joint by identifying their Fourier coefficients: global asymptotic and local exponential tracking of the input and output reference signals is obtained when the Fourier series expansion of each input reference signal is finite, while arbitrary small steady state tracking errors are achieved otherwise. The resulting controls are not model based and depend only on the period of the reference signals and on some constant bounds on the robot dynamics.
L’obiettivo di questa tesi è quello di progettare controllori adattativi ad apprendimento per sistemi non lineari, con non linearità dipendenti dall’uscita, e per manipolatori robotici. Inizialmente è stato progettato un controllore, in retroazione dall’errore di uscita, per sistemi non lineari (con non linearità regolari, incerte, dipendenti solo dal segnale di uscita e le cui costanti locali di Lipschitz siano note). I sistemi dinamici presi in considerazione devono essere osservabili, a fase minima, di grado relativo noto e con guadagno ad alta frequenza noto: i sistemi lineari sono compresi. Il segnale di riferimento di uscita deve essere regolare e periodico, con periodo noto. Sviluppando in serie di Fourier un opportuno segnale di riferimento periodico di ingresso, viene progettato un controllore adattativo ad apprendimento, in retroazione dall’errore di uscita, che apprende il riferimento di ingresso identificando i suoi coefficienti di Fourier. Quando l’espansione in serie di Fourier è finita, il controllore progettato garantisce che i segnali del sistema a ciclo chiuso siano limitati oltre ad un inseguimento esponenziale dei riferimenti di ingresso e di uscita. Invece quando l’espansione in serie di Fourier è infinita, vengono ottenuti errori di inseguimento asintotici arbitrariamente piccoli. Il controllore risultante non è basato sul modello, è indipendente dall’ordine del sistema e dipende solo dal grado relativo del sistema da controllare, dal periodo del segnale di riferimento e dal segno del guadagno ad alta frequenza. Le proprietà dei controlli adattativi ad apprendimento sono quindi studiate in riferimento ai manipolatori robotici, con giunti rotazionali e dinamica incerta, per i quali sono stati progettati un controllore in retroazione dallo stato ed uno in retroazione dall’errore di uscita. I segnali di riferimento da inseguire devono essere regolari e periodici (con periodo noto) oppure costanti. I due controllori, che sono stati progettati per i manipolatori robotica, apprendono la coppia di riferimento di ciascun giunto del manipolatore tramite l’identificazione dei loro coefficienti di Fourier. Quando l’espansione in serie di Fourier è finita, i due controllori garantiscono l’inseguimento globalmente asintotico e localmente esponenziale dei riferimenti di ingresso ed uscita. Quando invece l’espansione in serie di Fourier è infinita, vengono garantiti errori di inseguimento asintotici arbitrariamente limitati. Anche nel caso dei manipolatori robotici i controllori progettati non sono basati sul modello del sistema da controllare e dipendono solamente dal periodo del segnale di riferimento e da alcuni limiti costanti sulla dinamica del manipolatore robotico da controllare.
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Murphy, Ian Patrick. „Modeling and Control of Flapping Wing Robots“. Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/19275.
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The study of fixed wing aeronautical engineering has matured to the point where years of research result in small performance improvements. In the past decade, micro air vehicles, or MAVs, have gained attention of the aerospace and robotics communities. Many researchers have begun investigating aircraft schemes such as ones which use rotary or flapping wings for propulsion. While the engineering of rotary wing aircraft has seen significant advancement, the complex physics behind flapping wing aircraft remains to be fully understood. Some studies suggest flapping wing aircraft can be more efficient when the aircraft operates in low Reynolds regimes or requires hovering. Because of this inherent complexity, the derivation of flapping wing control methodologies remains an area with many open research problems. This thesis investigates flapping wing vehicles whose design is inspired by avian flight. The flapping wing system is examined in the cases where the core body is fixed or free in the ground frame. When the core body is fixed, the Denavit Hartenberg representation is used for the kinematic variables. An alternative approach is introduced for a free base body case. The equations of motion are developed using Lagranges equations and a process is developed to derive the aerodynamic contributions using a virtual work principle. The aerodynamics are modeled using a quasi-steady state formulation where the lift and drag coefficients are treated as unknowns. A collection of nonlinear controllers are studied, specifically an ideal dynamic inversion controller and two switching dynamic inversion controllers. A dynamic inversion controller is modified with an adaptive term that learns the aerodynamic effects on the equation of motion. The dissipative controller with adaptation is developed to improve performance. A Lyapunov analysis of the two adaptive controllers guarantees boundedness for all error terms. Asymptotic stability is guaranteed for the derivative error in the dynamic inversion controller and for both the position and derivative error in the dissipative controller. The controllers are simulated using two dynamic models based on flapping wing prototypes designed at Virginia Tech. The numerical experiments validate the Lyapunov analysis and illustrate that unknown parameters can be learned if persistently excited.Master of Science
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Zhao, Qingrong. „Reduced-Order Robust Adaptive Controller Design and Convergence Analysis for Uncertain SISO Linear Systems with Noisy Output Measurements“. University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1194564628.
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Khalili, Mohsen. „Distributed Adaptive Fault-Tolerant Control of Nonlinear Uncertain Multi-Agent Systems“. Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1503622016617833.
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Wang, Zhao. „Lyapunov-Based Control Design for Uncertain MIMO Systems“. Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5558.
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In this dissertation. we document the progress in the control design for a class of MIMO nonlinear uncertain system from five papers. In the first part, we address the problem of adaptive control design for a class of multi-input multi-output (MIMO) nonlinear systems. A Lypaunov based singularity free control law, which compensates for parametric uncertainty in both the drift vector and the input gain matrix, is proposed under the mild assumption that the signs of the leading minors of the control input gain matrix are known. Lyapunov analysis shows global uniform ultimate boundedness (GUUB) result for the tracking error under full state feedback (FSFB). Under the restriction that only the output vector is available for measurement, an output feedback (OFB) controller is designed based on a standard high gain observer (HGO) — stability under OFB is fostered by the uniformity of the FSFB solution. Simulation results for both FSFB and OFB controllers demonstrate the ef?cacy of the MIMO control design in the classical 2-DOF robot manipulator model. In the second part, an adaptive feedback control is designed for a class of MIMO nonlinear systems containing parametric uncertainty in both the drift vector and the input gain matrix, which is assumed to be full-rank and non-symmetric in general. Based on an SDU decomposition of the gain matrix, a singularity-free adaptive tracking control law is proposed that is shown to be globally asymptotically stable (GAS) under full-state feedback. Output feedback results are facilitated via the use of a high-gain observer (HGO). Under output feedback control, ultimate boundedness of the error signals is obtained &"241; the size of the bound is related to the size of the uncertainty in the parameters. An explicit upper bound is also provided on the size of the HGO gain constant. In third part, a class of aeroelastic systems with an unmodeled nonlinearity and external disturbance is considered. By using leading- and trailing-edge control surface actuations, a full-state feedforward/feedback controller is designed to suppress the aeroelastic vibrations of a nonlinear wing section subject to external disturbance. The full-state feedback control yields a uniformly ultimately bounded result for two-axis vibration suppression. With the restriction that only pitching and plunging displacements are measurable while their rates are not, a high-gain observer is used to modify the full-state feedback control design to an output feedback design. Simulation results demonstrate the ef ? cacy of the multi-input multi-output control toward suppressing aeroelastic vibration and limit cycle oscillations occurring in pre and post? utter velocity regimes when the system is subjected to a variety of external disturbance signals. Comparisons are drawn with a previously designed adaptive multi-input multi-output controller. In the fourth part, a continuous robust feedback control is designed for a class of high-order multi-input multi-output (MIMO) nonlinear systems with two degrees of freedom containing unstructured nonlinear uncertainties in the drift vector and parametric uncertainties in the high frequency gain matrix, which is allowed to be non-symmetric in general. Given some mild assumptions on the system model, a singularity-free continuous robust tracking control law is designed that is shown to be semi-globally asymptotically stable under full-state feedback through a Lyapunov stability analysis. The performance of the proposed algorithm have been verified on a two-link robot manipulator model and 2-DOF aeroelastic model.Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering
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Bennehar, Moussab. „Some contributions to nonlinear adaptive control of PKMs : from design to real-time experiments“. Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS033/document.
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La popularité des robots parallèles s’est considérablement accrue lors des dernières décennies. Cette popularité a été stimulée par les nombreux avantages qu’offrent les robots parallèles par rapport à leurs homologues traditionnels sériels concernant certaines applications industrielles nécessitant de fortes accélérations et une bonne précision. Toutefois, afin d'exploiter pleinement leur potentiel et de tirer le meilleur de leurs capacités, un long chemin reste encore à parcourir. En plus de la conception mécanique, l'étalonnage et l'optimisation de la structure, le développement d’une commande efficace joue un rôle primordial dans l’amélioration de la performance globale des robots parallèles. Cependant, ces derniers sont connus par leur dynamique fortement non linéaire qui s’accroît considérablement lorsque de fortes accélérations sont sollicitées conduisant à des vibrations mécaniques. En outre, les incertitudes sont abondantes dans ces systèmes en raison des hypothèses simplificatrices de modélisation, l'usure des composants du robot et les variations de l'environnement. De plus, leur dynamique couplée et la redondance d'actionnement dans certains mécanismes donnent lieu à des problèmes de commande complexes et difficiles à gérer. Par conséquent, les stratégies de commande développées pour les robots parallèles devraient tenir compte de tous les enjeux et défis mentionnées précédemment. L'objectif principal de cette thèse réside dans la proposition de nouvelles stratégies de commande adaptatives pour les robots parallèles tenant compte de leurs caractéristiques et particularités afin d'améliorer leurs performances de suivi de trajectoires. En outre, les stratégies de commande développées devraient être validées d'abord en simulation, puis à travers des expérimentations temps-réel sur les robots parallèles à notre disposition. Dans ce contexte, trois contributions majeures sont proposées dans le cadre de cette thèse. Tout d'abord, une nouvelle classe de contrôleurs adaptatifs avec des gains de retour non linéaires temps-variant est proposée. La deuxième contribution réside dans le développement d’une version adaptative de la commande robuste RISE. Pour la troisième contribution, la stratégie de commande adaptative L1, récemment développée, est appliquée pour la première fois sur un robot parallèle, suivie de deux nouvelles extensions basées-modèle. Des simulations numériques ainsi que des expérimentations temps-réel sur différents prototypes de robots parallèles sont présentées et discutées. Tous les contrôleurs proposés sont validés pour différents scénarios permettant ainsi de montrer leur pertinence et efficacitéParallel Kinematic Manipulators (PKMs) have gained an increased popularity in the last few decades. This interest has been stimulated by the significant advantages of PKMs compared to their traditional serial counterparts, with respect to some specific industrial tasks requiring high accelerations and accuracy. However, to fully exploit their potential and to get the most of their capabilities, a long path is still to be covered. In addition to mechanical design, calibration and optimization of the structure, efficient control development plays an essential role in improving the overall performance of PKMs. However, PKMs are known for their highly nonlinear dynamics which increases considerably when operating at high accelerations leading to mechanical vibrations. Moreover, uncertainties are abundant in such systems due to model simplifications, the wear of the components of the robot and the variations of the environment. Furthermore, their coupled dynamics and actuation redundancy in some mechanisms give rise to complex and challenging control issues. Consequently, the developed control schemes should take into account all the previously mentioned issues and challenges. The main goal of this thesis lies in the proposal of new adaptive control schemes for PKMs while considering their characteristics and particularities in order to improve their tracking capabilities. Moreover, the developed control strategies should be first validated through numerical simulations, then through real-time experiments on available PKMs. Within this context, three main contributions are proposed in this thesis. First, a new class of adaptive controllers with nonlinear time-varying feedback gains is proposed. The second contribution lies in an adaptive-based extended version of RISE robust feedback control strategy. For the third contribution, the recently developed L1 adaptive control strategy is applied for the first time on a PKM, followed by two novel model-based extensions. Numerical simulations as well as real-time experiments on various PKMs prototypes are provided and discussed. All the proposed controllers are validated for different operating conditions in order to show their relevance and efficiency
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Mehmood, Adeel. „Modeling, simulation and robust control of an electro-pneumatic actuator for a variable geometry turbocharger“. Phd thesis, Université de Technologie de Belfort-Montbeliard, 2012. http://tel.archives-ouvertes.fr/tel-00827445.
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The choice of technology for automotive actuators is driven by the need of high power to size ratio. In general, electro-pneumatic actuators are preferred for application around the engine as they are compact, powerful and require simple controlling devices. Specially, Variable Geometry Turbochargers (VGTs) are almost always controlled with electro-pneumatic actuators. This is a challenging application because the VGT is an important part of the engine air path and the latter is responsible for intake and exhaust air quality and exhaust emissions control. With government regulations on vehicle pollutant emissions getting stringent by the year, VGT control requirements have also increased. These regulations and requirements can only be fulfilled with precise dynamic control of the VGT through its actuator. The demands on actuator control include robustness against uncertainty in operating conditions, fast and smooth positioning without vibration, limited number of measurements. Added constraints such as nonlinear dynamic behavior of the actuator, friction and varying aerodynamic forces in the VGT render classical control methods ineffective. These are the main problems that form the core of this thesis.In this work, we have addressed the above mentioned problems, using model based control complemented with robust control methods to overcome operational uncertainties and parametric variations. In the first step, a detailed physical model of an electro-pneumatic actuator has been developed; taking into account the nonlinear characteristics originating from air compressibility and friction. Means to compensate for aerodynamic force have been studied and implemented in the next step. These include model parametric adaptation and one dimensional CFD (Computational Fluid Dynamics) modeling. The complete model has been experimentally validated and a sensitivity analysis has been conducted to identify the parameters which have the greatest impact upon the actuator's behavior. The detailed simulation model has then been simplified to make it suitable for control purposes while keeping its essential behavioral characteristics (i.e. transients and dynamics). Next, robust controllers have been developed around the model for the control objective of accurate actuator positioning in presence of operational uncertainty. An important constraint in commercial actuators is that they provide output feedback only, as they are only equipped with low-cost position sensors. This hurdle has been overcome by introducing observers in the control loop, which estimate other system states from the output feedback. The estimation and control algorithms have been validated in simulation and experimentally on diesel engine test benches.
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Karasalo, Maja. „Data Filtering and Control Design for Mobile Robots“. Doctoral thesis, KTH, Optimeringslära och systemteori, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11011.
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In this thesis, we consider problems connected to navigation and tracking for autonomousrobots under the assumption of constraints on sensors and kinematics. We study formation controlas well as techniques for filtering and smoothing of noise contaminated input. The scientific contributions of the thesis comprise five papers.In Paper A, we propose three cascaded, stabilizing formation controls for multi-agent systems.We consider platforms with non-holonomic kinematic constraints and directional rangesensors. The resulting formation is a leader-follower system, where each follower agent tracksits leader agent at a specified angle and distance. No inter-agent communication is required toexecute the controls. A switching Kalman filter is introduced for active sensing, and robustnessis demonstrated in experiments and simulations with Khepera II robots.In Paper B, an optimization-based adaptive Kalman filteringmethod is proposed. The methodproduces an estimate of the process noise covariance matrix Q by solving an optimization problemover a short window of data. The algorithm recovers the observations h(x) from a system˙ x = f (x), y = h(x)+v without a priori knowledge of system dynamics. The algorithm is evaluatedin simulations and a tracking example is included, for a target with coupled and nonlinearkinematics. In Paper C, we consider the problem of estimating a closed curve in R2 based on noisecontaminated samples. A recursive control theoretic smoothing spline approach is proposed, thatyields an initial estimate of the curve and subsequently computes refinements of the estimateiteratively. Periodic splines are generated by minimizing a cost function subject to constraintsimposed by a linear control system. The optimal control problem is shown to be proper, andsufficient optimality conditions are derived for a special case of the problem using Hamilton-Jacobi-Bellman theory.Paper D continues the study of recursive control theoretic smoothing splines. A discretizationof the problem is derived, yielding an unconstrained quadratic programming problem. Aproof of convexity for the discretized problem is provided, and the recursive algorithm is evaluatedin simulations and experiments using a SICK laser scanner mounted on a PowerBot from ActivMedia Robotics. Finally, in Paper E we explore the issue of optimal smoothing for control theoretic smoothingsplines. The output of the control theoretic smoothing spline problem is essentially a tradeoff between faithfulness to measurement data and smoothness. This tradeoff is regulated by the socalled smoothing parameter. In Paper E, a method is developed for estimating the optimal valueof this smoothing parameter. The procedure is based on general cross validation and requires noa priori information about the underlying curve or level of noise in the measurements.QC 20100722
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Magnani, Guido. „Advanced satellite attitude control strategies under actuation constraints and multiple sources of disturbance“. Electronic Thesis or Diss., Toulouse, ISAE, 2024. http://depozit.isae.fr/theses/2024/2024_Magnani_Guido_D.pdf.
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Dans un scénario de satellites géostationnaires hautement autonomes, dotés de capacités d'auto-assemblage et d'auto-maintenance, les perturbations des bras manipulateurs couplées à la dynamique de ballotement du carburant représentent un risque significatif de dégradation des performances du système de contrôle d'attitude et d'orbite du satellite. Bien que des solutions passives existent pour amortir le ballotement du carburant et compenser les perturbations des bras manipulateurs, il manque une solution de contrôle actif unique capable de compenser ces perturbations tout en évitant de manière optimale la saturation des actionneurs. Cette lacune suscite un grand intérêt dans l'industrie spatiale en raison de ses implications potentielles dans la réduction du poids, des coûts et de la complexité de la fabrication.Cette étude explore l'intégration de techniques de contrôle robuste basées sur la synthèse $H_{infty}$ et de techniques de contrôle adaptatif par modèle de référence avec des schémas de reference governor. L'objectif est de proposer une solution de contrôle unique garantissant un contrôle précis de l'attitude du satellite en présence de perturbations non modélisées et de contraintes des actionneurs. Les avancées théoriques de cette recherche s'étendent également à des scénarios tels que la gestion des défaillances de propulseur dans les quadricoptères sous contraintes d'état et d'entrée, ainsi qu'à l'optimisation de la conception des modes de guidage pour des missions satellitaires telles que la mission Microcarb du CNESIn a scenario of highly autonomous geostationary satellites, with self-assembly and self-maintenance capabilities, manipulator arms perturbations coupled with fuel slosh dynamics represents a significant risk of performance degradation for the satellite attitude and orbit control system. While passive fuel slosh damping solutions and manipulator arm disturbances compensators exist by their own, a unique active control solution capable of rejecting the perturbations while optimally preventing the actuators saturation is lacking and of great interest in the space industry for weight, cost and complexity of manufacturing reduction. This study explores the integration of $H_{infty}$-based robust control and model reference adaptive control techniques with reference governor schemes. The objective is to propose a unique control solution to guarantee precise satellite attitude control in the presence of unmodeled perturbations and actuator constraints. The theoretical advancements from this research also extend to scenarios such as handling propeller failures in quadrotors under state and input constraints and optimizing the design of the guidance modes for satellite missions like the CNES Microcarb mission
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VERRELLI, CRISTIANO MARIA. „NON LINEAR CONTROL DESIGN FOR INDUCTION MOTORS AND SYNCHRONOUS GENERATORS“. Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2005. http://hdl.handle.net/2108/179.
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La tesi presenta recenti sviluppi nel progetto di leggi di controllo non lineari per motori ad induzione e generatori sincroni: tecniche di controllo robuste, adattative, in retroazione dallo stato o dall'uscita sono utilizzate per tali sistemi elettromeccanici descritti da equazioni differenziali ordinarie, deterministiche e
¯nito-dimensionali e possibilmente caratterizzati da incertezze come parametri non noti (costanti o tempovarianti).
I motori ad induzione, che, grazie alla loro più semplice struttura, sono più affidabili e meno costosi di quelli a magneti permanenti, a riluttanza variabile e in corrente continua, sono difficili da controllare per diverse ragioni: le dinamiche sono intrinsecamente non lineari e multivariabile (due ingressi di controllo e due uscite da controllare) ; non tutte le variabili di stato e non tutte le uscite da controllare possono essere disponibili per la retroazione; sono presenti parametri critici incerti, come la coppia di carico, tipicamente non nota in tutti i motori elettrici e la resistenza rotorica, che può variare fino al 100 % durante il funzionamento a causa del riscaldamento del rotore. La disponibilità di potenti DSP a basso costo e i
progressi nell'elettronica di potenza hanno reso algoritmi complessi implementabili anche per motori ad induzione di media e piccola taglia, che, in tal modo, sono effettivamente in grado di sostituire i motori elettrici usati, ammesso che siano garantite alte prestazioni dinamiche ed elevata e±cienza: ciò ha motivato intensi sforzi di ricerca nel progetto di controllori non lineari per motori ad induzione.
In modo analogo, la stabilizzazione transitoria e la regolazione della tensione per sistemi di potenza sono problemi di controllo classicamente di±cili: tutti i modelli dinamici che sono stati proposti per una singola macchina connessa a un in ¯ n ite bu s mostrano una intrinseca natura non lineare e, di conseguenza, diversi punti di equilibrio stabili e instabili. Primi studi miravano alla determinazione di regioni di stabilità delle condizioni operative desiderate, via funzioni di Lyapunov, cosi da studiare l'effetto delle improvvise perturbazioni meccaniche e elettriche che possono destabilizzare il sistema e forzare il singolo generatore
ad essere disconnesso dalla rete. Il problema consiste dunque nel mantenere la velocità del generatore prossima alla velocità sincrona quando perturbazioni occorrono (stabilizzazione transitoria) e regolare la tensione di uscita al corrispondente valore di riferimento nel caso di perturbazioni costanti e permanenti (regolazione della tensione in uscita). A tal riguardo, i controllori lineari realmente impiegati, progettati sulla base di approssimazioni lineari attorno alle condizioni operative, non sono in grado di sostenere le forti perturbazioni che tipicamente occorrono nei sistemi di potenza: controllori non lineari sono di conseguenza
richiesti.
La tesi è suddivisa in due parti: la prima parte (motore ad induzione) è formata dai capitoli 2, 3 e 4, mentre la seconda parte (generatore sincrono) consiste dei capitoli 5 e 6. I capitoli 2 e 3 affrontano il problema del controllo di motori ad induzione senza sensore di velocità: l'esistenza di uno schema di controllo globale è esplorata nel capitolo 2 mentre una legge di controllo non lineare adattativa è progettata nel capitolo 3. Il capitolo 4 è dedicato al progetto di un controllore non lineare per motori ad induzione
sen so rless: uno schema di controllo in retroazione dall'uscita è proposto. I capitoli 5 e 6 concernono il problema del controllo di un generatore sincrono con incertezze nei parametri: nel capitolo 5, un controllore non lineare robusto adattativo è presentato per la stabilizzazione transitoria, mentre il capitolo 6 propone
una legge di controllo non lineare robusta adattativa che garantisce sia stabilizzazione transitoria che regolazione della tensione in uscita.The thesis incorporates recent advances in the design of nonlinear control laws for induction motors and synchronous generators: robust, adaptive, state or output feedback control techniques are used for both these electro-mechanical systems which are modelled by ¯nite dimensional, deterministic ordinary differential equations and are possibly affected by uncertainties, such as unknown constant and time-varying parameters. Induction motors, which, due to their simpler construction, are more reliable and less expensive than those permanent magnet, switched reluctance and d.c. motors are di±cult to control for several reasons: their dynamics are intrinsically nonlinear and multivariable (two control inputs and two outputs to be controlled); not all of the state variables and not all of the outputs to be controlled may be available for feedback; there are critical uncertain parameters such as load torque, which is typically unknown in all electrical drives, and rotor resistance, which, due to rotor heating, may vary up to 100% during operations. The availability of low cost powerful digital signal processors and advances in power electronics made complex algorithms implementable even for medium- and small-size induction motors, which, in this way, could replace currently used motors provided that high dynamic tracking performance along with highpower efficiency are achieved: this is what motivated intense research efforts in induction motor control design. In analogous way, transient stabilization and voltage regulation for power systems are classically difficult control problems: all the dynamic models which have been developed for a single machine connected to an in¯nite bus show an intrinsic nonlinear nature and, consequently, there are several stable and unstable equilibrium points. Early studies aimed at determining the stability regions of desired operating conditions by means of Lyapunov functions in order to study the effect of perturbations. In fact, sudden mechanical and electrical perturbations may drive the system outside its stability region and force the generator to be disconnected from the network. The transient stabilization and voltage regulation problem consists in the design of an excitation control which keeps the generator speed close to the synchronous speed when perturbations occur (transient stabilization) and regulates the output voltage to the corresponding reference value in the case of permanent constant perturbations (voltage regulation). To this purpose, linear controllers are actually employed which are designed on the basis of linear approximations around operating conditions: only small perturbations and deviations from operating conditions can be handled. It is clear that nonlinear controllers are required to handle the large perturbations that typically occur in power systems. The thesis is divided into two parts: Part I (induction motor) consists of Chapters 2, 3 and 4 while Part II (synchronous generator) consists of Chapters 5 and 6. Chapters 2 and 3 address the problem of controlling a speed-sensorless induction motor: the existence of a global controller is explored in Chapter 2, while a nonlinear adaptive control scheme is developed in Chapter 3. Chapter 4 is devoted to nonlinear control design for a sensorless induction motor: an output feedback control algorithm is proposed. Chapters 5 and 6 address the problem of controlling a synchronous generator with parameter uncertainty: a nonlinear robust adaptive transient stabilizing control is presented in Chapter 5, while Chapter 6 proposes a nonlinear robust adaptive transient stabilizing and output regulating control algorithm.
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Sartori, Natal Guilherme. „Control of parallel robots : towards very high accelerations“. Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20085/document.
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L'objectif principal de ce travail est de proposer des approches de commande performantes et robustes aux incertitudes pour les robots parallèles de type Delta, qui sont conçus pour effectuer des tâches industriels importantes et exigeantes comme l'emballage en agroalimentaire, la découpe laser, etc. Les difficultés les plus importantes pour garantir une bonne performance de suivi de trajectoires de ces manipulateurs pour les hautes accélérations avec la meilleure précision possible, tout en conservant de telle performance indépendamment des conditions d'opération (par exemple avec différentes conditions de charge, différentes trajectoires, etc.) sont leur actionnement couplé, l'augmentation de leurs dynamiques non-linéaires et le problème de vibrations mécaniques avec l'augmentation des accélérations envisagées, la présence d'incertitudes sur le modèle/environnement et la redondance d'actionnement si elle existe. Dans cette thèse, différentes approches de commande et observateurs d'état ont été proposés et implémentés expérimentalement sur deux robots de type Delta, à savoir le Par2 (non-redondant) et le R4 (à redondance d'actionnement). Pour le premier, une commande non linéaire/adaptative à mode Dual a été proposée en espace articulaire, synthétisé avec trois différents observateurs d'état pour la estimation des vitesses articulaires: un observateur lead-lag, un observateur Alpha-bêta-gamma et un observateur à grand gain. Pour le robot R4, un commande à feedforward en espace-dual avec a été proposée pour la compensation de sa dynamique (avec laquelle une aaccélération maximale de 100G a été atteinte), puis un contrôleur adaptatif dans l'espace-dual a été proposé afin de garantir une estimation et mise à jours automatique des paramètres du système en temps réel, garantissant ainsi sa bonne performance indépendamment du scénario expérimental. L'analyse de stabilité du robot Par2 bouclé avec la commande adaptative à Mode Dual et du robot R4 commandé avec le contrôleur adaptatif dans l'espace-dual sont fournies, des simulations ont été effectuées et les résultats expérimentaux confirment la bonne performance des approches de commande proposéesThe main objective of this work is to propose control strategies performant and robust towards uncertainties for Delta-like parallel robots, which are designed to perform important and demanding industrial tasks, such as packaging, laser cutting, etc. The most important difficulties to guarantee the good tracking performance of these manipulators for very high accelerations with the best possible precision, while maintaining such performance independently of the operational case (e.g. with different load conditions, different trajectories, etc.) are their coupled actuation, the increase of their high nonlinear dynamics and the problem of mechanical vibrations with the increase of the involved accelerations, the presence of uncertainties in the model/environment and the redundant actuation when applicable. In this thesis, different control schemes and state observers were proposed and experimentally implemented on two Delta-like robots, namely the Par2 (non-redundant) and the R4 (redundantly actuated) parallel manipulators. For the former, a nonlinear/adaptive Dual Mode controller was proposed in the joint space, complied with three different state observers for the estimation of joint velocities: a Lead-lag based observer, an Alpha-beta-gamma observer and the High-gain observer. For the latter, firstly a dual-space feedforward controller was proposed for the compensation of its dynamics (with which a maximum of 100G of acceleration was reached), then a dual-space adaptive controller was proposed in order to automatically estimate the parameters of the system in real-time, thus guaranteeing its good performance independently of the experimental scenario. The stability analysis of Par2 robot under the control of the Dual Mode controller and the R4 robot under the control of the dual-space adaptive controller are provided, simulations were performed and the experimental results confirm the good performance of the proposed control schemes
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Basbas, Hedi. „Commandes non linéaires robustes et adaptatives des éoliennes flottantes“. Electronic Thesis or Diss., Bourgogne Franche-Comté, 2023. http://www.theses.fr/2023UBFCA022.
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L’industrie éolienne, ayant optimisé les technologies terrestres, se tourne vers les vents marins qui offrent plus de vitesse et moins de turbulence. Les éoliennes flottantes (EF), souvent ancrées dans des eaux de plus de 30 m de profondeur, reposent sur des bases flottantes pour des raisons de coût. Ces plateformes sont confrontées à des défis liés aux perturbations et dynamiques complexes dues à l'interaction entre vents et vagues. Ainsi, la conception de systèmes de contrôle adaptatifs et robustes est indispensable pour gérer ces défis spécifiques aux éoliennes flottantes. Ce travail de thèse vise à atteindre trois objectifs majeurs. En premier lieu, il a pour but d'élaborer un modèle non linéaire pour les éoliennes flottantes, plus précisément un modèle orienté commande, qui est essentiel pour la mise au point de systèmes de commande efficaces. Le deuxième objectif se focalise sur la synthèse de lois de commande stables, robustes et adaptatives, élaborées en se basant sur le modèle non linéaire précédemment développé. Enfin, le troisième objectif concerne la création d’une plateforme HIL spécifique aux éoliennes flottantes, conçue pour tester et valider les lois de commande en temps réel. Ainsi, nous avons développé un modèle non linéaire entièrement analytique, essentiel à la synthèse de commandes non linéaires, marquant une contribution significative de cette thèse. Utilisant ce modèle, divers contrôleurs par mode glissant à gains fixes ont été élaborés pour la région 3 de fonctionnement, où la vitesse du vent est assez élevée pour permettre à la génératrice d'atteindre sa vitesse nominale. Dans ce contexte, les contrôleurs sont conçus pour ajuster l'angle des pales afin d'assurer la stabilité de la plateforme, en particulier l'angle de tangage, et pour maximiser la production d'électricité. Ils maintiennent également la vitesse de la génératrice au niveau nominal avec une oscillation minimale, réduisant ainsi la fatigue de la structure, des pales et des lignes caténaires. Ces travaux ont démontré les performances et la capacité des commandes par mode glissant à gains fixes pour les EF à travers une comparaison avec un contrôleur de référence dans la littérature. C’est pourquoi, dans un second temps, plusieurs commandes par mode glissant adaptatives ont été mises en oeuvre afin d'outrepasser les performances du contrôleur de référence. Finalement, le principal défi de cette thèse a été l’émulation en temps réel du simulateur haute-fidélité OpenFAST pour les EF sur une carte de développement. Le document décrit minutieusement le processus d'émulation sur une carte compactRIO de National Instruments. Il guide le lecteur depuis la phase de sélection des cartes, en traversant les étapes complexes de compilation et de modification des codes informatiques, jusqu'à l'achèvement de la plateforme Hardware-In-the-LoopHaving optimized terrestrial technologies, the wind industry is now turning to marine winds, which offer greater speed and less turbulence. Floating wind turbines (FWTs), often anchored in waters over 30 m deep, rely on floating bases for cost reasons. These platforms face challenges related to the complex disturbances and dynamics caused by the interaction between wind and waves. Thus, the design of adaptive and robust control systems is essential to manage these challenges specifically to floating wind turbines. This thesis aims to achieve three major objectives. Firstly, it aims to develop a nonlinear model for floating wind turbines, specifically control-oriented model, which is essential for the development of efficient control systems. The second objective focuses on the synthesis of stable, robust and adaptive control laws, based on the previously developed nonlinear model. Finally, the third objective concerns the creation of a HIL platform specific to floating wind turbines, designed to test and validate the control laws in real time. In this way, we have developed a fully analytical nonlinear model, essential for the synthesis of nonlinear controls, marking a significant contribution of this thesis. Using this model, various fixed gain sliding-mode controllers were developed for operating region 3, where the wind speed is high enough to allow the generator to reach its rated speed. In this context, the controllers are designed to adjust the blade angle to ensure platform stability, in particular the pitch angle, and to maximize electricity production. They also maintain generator speed at nominal levels with minimal oscillations, thus reducing fatigue on the structure, blades and catenary lines. This work demonstrated the performance and capability of fixed-gain sliding-mode controls for EFs through a comparison with a reference controller in the literature. Therefore, in a second step, several adaptive sliding mode controllers were implemented in order to outperform the reference controller. Finally, the main challenge of this thesis was the real-time emulation of the OpenFAST high-fidelity simulator for EFs on a development board. The paper describes in detail the emulation process on a National Instruments compactRIO board. It guides the reader from the board selection phase, through the complex stages of compiling and modifying computer code, to the completion of the hardware-in-the-loop platform
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Fu, Ye. „Robust adaptive control“. Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/30574.
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This thesis describes discrete robust adaptive control methods based on using slow sampling and slow adaptation. For the stability analysis, we consider that the plant model order is not exactly known and assume that the estimation model order is lower than the plant model order. A stability condition is derived with a given upper limit for the adaptation gain which is related to a strictly positive real operator. Discussion of the relation between sampling and stability condition is then given. For the robust adaptive control design, we study slow adaptation and predictive control. For the slow adaptation, the main idea is to use only good estimates and use a compensation filter. Some frequency domain information on the plant is necessary for this method. For predictive control, we discuss the relationship between the extended control horizon and the critical sampling. For a simple case, it is shown that the larger extended control horizon brings more robust adaptive control.
The purpose of this thesis is to provide robust discrete adaptive controller design guidelines, especially in such cases as using slow sampling frequency, slow adaptation rate. It is true that in practice, for various discrete adaptive control algorithms, slow sampling and slow adaptation rate will bring more robustness. The use of slow sampling and slow adaptation rate is simple and economic, thus a careful choice of sampling rate and adaptation rate is highly recommended. This thesis provides such guidelines for choosing proper sampling rate and adaptation rate for robust discrete adaptive control.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Fahmy, Sherif Farid Fahmy. „Nonlinear robust H∞ control“. Thesis, University of Sheffield, 2006. http://etheses.whiterose.ac.uk/14887/.
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A new theory is proposed for the full-information finite and infinite horizontime robust H∞ control that is equivalently effective for the regulation and/or tracking problems of the general class of time-varying nonlinear systems under the presence of exogenous disturbance inputs. The theory employs the sequence of linear-quadratic and time-varying approximations, that were recently introduced in the optimal control framework, to transform the nonlinear H∞ control problem into a sequence of linearquadratic robust H∞ control problems by using well-known results from the existing Riccati-based theory of the maturing classical linear robust control. The proposed method, as in the optimal control case, requires solving an approximating sequence of Riccati equations (ASRE), to find linear time-varying feedback controllers for such disturbed nonlinear systems while employing classical methods. Under very mild conditions of local Lipschitz continuity, these iterative sequences of solutions are known to converge to the unique viscosity solution of the Hamilton-lacobi-Bellman partial differential equation of the original nonlinear optimal control problem in the weak form (Cimen, 2003); and should hold for the robust control problems herein. The theory is analytically illustrated by directly applying it to some sophisticated nonlinear dynamical models of practical real-world applications. Under a r -iteration sense, such a theory gives the control engineer and designer more transparent control requirements to be incorporated a priori to fine-tune between robustness and optimality needs. It is believed, however, that the automatic state-regulation robust ASRE feedback control systems and techniques provided in this thesis yield very effective control actions in theory, in view of its computational simplicity and its validation by means of classical numerical techniques, and can straightforwardly be implemented in practice as the feedback controller is constrained to be linear with respect to its inputs.
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Yoon, Tae-Woong. „Robust adaptive predictive control“. Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359527.
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Samavat, Mohmoud. „Robust control of nonlinear systems“. Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327647.
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Rysdyk, Rolf T. „Adaptive nonlinear flight control“. Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/12108.
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Munnae, Jomkwun. „Uncalibrated robotic visual servo tracking for large residual problems“. Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37219.
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In visually guided control of a robot, a large residual problem occurs when the robot configuration is not in the neighborhood of the target acquisition configuration. Most existing uncalibrated visual servoing algorithms use quasi-Gauss-Newton methods which are effective for small residual problems. The solution used in this study switches between a full quasi-Newton method for large residual case and the quasi-Gauss-Newton methods for the small case. Visual servoing to handle large residual problems for tracking a moving target has not previously appeared in the literature.
For large residual problems various Hessian approximations are introduced including an approximation of the entire Hessian matrix, the dynamic BFGS (DBFGS) algorithm, and two distinct approximations of the residual term, the modified BFGS (MBFGS) algorithm and the dynamic full Newton method with BFGS (DFN-BFGS) algorithm. Due to the fact that the quasi-Gauss-Newton method has the advantage of fast convergence, the quasi-Gauss-Newton step is used as the iteration is sufficiently near the desired solution. A switching algorithm combines a full quasi-Newton method and a quasi-Gauss-Newton method. Switching occurs if the image error norm is less than the switching criterion, which is heuristically selected.
An adaptive forgetting factor called the dynamic adaptive forgetting factor (DAFF) is presented. The DAFF method is a heuristic scheme to determine the forgetting factor value based on the image error norm. Compared to other existing adaptive forgetting factor schemes, the DAFF method yields the best performance for both convergence time and the RMS error.
Simulation results verify validity of the proposed switching algorithms with the DAFF method for large residual problems. The switching MBFGS algorithm with the DAFF method significantly improves tracking performance in the presence of noise. This work is the first successfully developed model independent, vision-guided control for large residual with capability to stably track a moving target with a robot.
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Bekit, Biniam Weldai. „Robust nonlinear control of robot manipulators“. Thesis, King's College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321945.
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Chudoung, Jerawan. „Robust Control for Hybrid, Nonlinear Systems“. Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26983.
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We develop the robust control theories of stopping-time nonlinear systems and switching-control nonlinear systems. We formulate a robust optimal stopping-time control problem for a state-space nonlinear system and give the connection between various notions of lower value function for the associated game (and storage function for the associated dissipative system) with solutions of the appropriate variational inequality (VI). We show that the stopping-time rule can be obtained by solving the VI in the viscosity sense. It also happens that a positive definite supersolution of the VI can be used for stability analysis. We also show how to solve the VI for some prototype examples with one-dimensional state space.
For the robust optimal switching-control problem, we establish the Dynamic Programming Principle (DPP) for the lower value function of the associated game and employ it to derive the appropriate system of quasivariational inequalities (SQVI) for the lower value vector function. Moreover we formulate the problem in the L2-gain/dissipative system framework. We show that, under appropriate assumptions, continuous switching-storage (vector) functions are characterized as viscosity supersolutions of the SQVI, and that the minimal such storage function is equal to the lower value function for the game. We show that the control strategy achieving the dissipative inequality is obtained by solving the SQVI in the viscosity sense; in fact this solution is also used to address stability analysis of the switching system. In addition we prove the comparison principle between a viscosity subsolution and a viscosity supersolution of the SQVI satisfying a boundary condition and use it to give an alternative derivation of the characterization of the lower value function. Finally we solve the SQVI for a simple one-dimensional example by a direct geometric construction.Ph. D.
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Barbosa, William de Souza. „Controle de um sistema de eletroestimulação funcional“. Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=8133.
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Esta Dissertação irá apresentar a utilização de técnicas de controle nãolinear,
tais como o controle adaptativo e robusto, de modo a controlar um sistema de
Eletroestimulação Funcional desenvolvido pelo laboratório de Engenharia Biomédica
da COPPE/UFRJ. Basicamente um Eletroestimulador Funcional (Functional
Electrical Stimulation FES) se baseia na estimulação dos nervos motores via
eletrodos cutâneos de modo a movimentar (contrair ou distender) os músculos,
visando o fortalecimento muscular, a ativação de vias nervosas (reinervação),
manutenção da amplitude de movimento, controle de espasticidade muscular,
retardo de atrofias e manutenção de tonicidade muscular. O sistema utilizado tem
por objetivo movimentar os membros superiores através do estímulo elétrico de
modo a atingir ângulos-alvo pré-determinados para a articulação do cotovelo. Devido
ao fato de não termos conhecimento pleno do funcionamento neuro-motor humano e
do mesmo ser variante no tempo, não-linear, com parâmetros incertos, sujeito a
perturbações e completamente diferente para cada indivíduo, se faz necessário o
uso de técnicas de controle avançadas na tentativa de se estabilizar e controlar esse
tipo de sistema. O objetivo principal é verificar experimentalmente a eficácia dessas
técnicas de controle não-linear e adaptativo em comparação às técnicas clássicas,
de modo a alcançar um controle mais rápido, robusto e que tenha um desempenho
satisfatório. Em face disso, espera-se ampliar o campo de utilização de técnicas de
controle adaptativo e robusto, além de outras técnicas de sistemas inteligentes, tais
como os algoritmos genéticos, provando que sua aplicação pode ser efetiva no
campo de sistemas biológicos e biomédicos, auxiliando assim na melhoria do
tratamento de pacientes envolvidos nas pesquisas desenvolvidas no Laboratório de
Engenharia Biomédica da COPPE/UFRJ.This dissertation will present the use of nonlinear control techniques, such as adaptive and robust control in order to design a Functional Electrical Stimulation (FES) system developed by Biomedical Engineering Laboratory at COPPE/UFRJ. Basically, a FES on the stimulation of motor nerves via skin electrodes in order to contract or stretch the muscles such that the amplitude and quality of the limbs movement can be maintained, reducing muscular atrophy as well. Consequently, the muscle strength can be improved and new neural pathways may be activated. Here, the goals of the proposed control system is to move the arm of the patient via electrical stimulation to achieve some desired trajectory related to the elbow angles of reference. Since we have a priori no deep knowledge of human neuro-motor model, the use of advanced and robust control schemes seems to be useful to stabilize this kind of systems which may be completely different for each individual, being time-varying, nonlinear, uncertain and subject to disturbances. The main objective is to experimentally verify the effectiveness of the proposed nonlinear and adaptive controllers when compared to classical ones in order to achieve faster, robust and better control performance. It is expected to spread the application of adaptive and robust controllers and other intelligent system tools, such as genetic algorithms, to the field of biological and biomedical engineering. Thus, we believe that the developed control system may help the improvement of the patients treatment involved in the research carried out by Biomedical Engineering Laboratory at COPPE/UFRJ.
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Ydstie, Birger Erik. „Robust adaptive control of chemical processes“. Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/8295.
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Marriott, Jack. „Adaptive robust fuzzy logic control design“. Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/15819.
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Cantalloube, Hubert. „Robust adaptive control : a Bezout approach“. Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=74272.
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An adequate definition of stability for linear, discrete time, invariant, infinite order systems, and factorization properties in the corresponding space of transfer functions, lead to the design of finite order robust controllers. Moreover, this class of controllers is shown to stabilize stochastic systems.The stabilization by a class of robust adaptive controllers, of non-necessarily minimum phase stochastic linear systems (with possibly unknown or heterogeneous delay) is proved. The plants considered may be slowly time varying.
Simulations permit to emphasize the interest of our approach. Compared with the standard Recursive Least Squares and Stochastic Gradient Algorithms, the algorithm we introduce, is more satisfying.
Compared with fixed control techniques such as H$ sp infty$-optimization, the adaptive control is shown to have at least a wider range of use, but lower performances.
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Song, Qing. „Design of robust adaptive control systems“. Thesis, University of Strathclyde, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.331971.
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El-Rifai, Khalid 1979. „Robust adaptive control of switched systems“. Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39897.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (leaves 141-149).
In this thesis, robust adaptive controllers are developed for classes of switched nonlinear systems. Switched systems are those governed by differential equations, which undergo vector field switching due to sudden changes in model characteristics. Such systems arise in many applications such as mechanical systems with contacts, electrical systems with switches, and thermal-fluidic systems with valves and phase changes. The presented controllers guarantee system stability, under typical adaptive control assumptions, for systems with piecewise differentiable bounded parameters and piecewise continuous disturbances without requiring a priori knowledge on such parameters or disturbances. The effect of plant variation and switching is reduced to piecewise continuous and impulsive inputs acting on a Bounded Input Bounded State (BIBS) stable closed loop system. This, in turn, provides a separation between the robust stability and robust performance control problems. The developed methodology provides clear guidelines for steady-state and transient performance optimization and allows for parameter scheduling and multiple model controller adjustment techniques to be utilized with no stability concerns. The results are illustrated for various systems including contact-based robotic manipulation and Atomic Force Microscope (AFM) based nano-manipulation.
by Khalid El Rifai.
Ph.D.
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Watanabe, Yoko. „Stochastically optimized monocular vision-based navigation and guidance“. Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/22545.
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Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2008.Committee Chair: Johnson, Eric; Committee Co-Chair: Calise, Anthony; Committee Member: Prasad, J.V.R.; Committee Member: Tannenbaum, Allen; Committee Member: Tsiotras, Panagiotis.
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Walchko, Kevin J. „Robust nonlinear attitude control with disturbance compensation“. [Gainesville, Fla.]: University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0000818.
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Yao, Liqun. „Robust nonlinear tracking control of robotic manipulators“. Thesis, University of Leicester, 1999. http://hdl.handle.net/2381/30175.
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This thesis has discussed the development and implementation of robust nonlinear tracking control for a parallel and serial topology Tetrahedral robot (Tetrabot), although the theoretical control strategy presented is applicable to any manipulator tracking problem. The design of robust tracking controllers involves deriving a tracking law for uncertain dynamic systems, such that the actual positions closely track desired trajectories. Two new schemes, a robust sliding mode control and a Lyapunov-based robust tracking control, have been presented for uncertain dynamical systems in the presence of model uncertainty and disturbances. The foci of this study are the concepts and techniques of robust nonlinear tracking control with a bias toward industrial applications. The Tetrabot system structure, hardware, software and the results of implementation on the three degree of freedom parallel geometry have been studied. In order to implement robust tracking control laws, the Tetrabot system software has been further developed. Most importantly, the results of implementation of a nonlinear tracking controller on the Tetrabot rig facility are also studied. To demonstrate the performance attainable by this control strategy, the trajectory involved movement across the primary working volume to the end-effect point which is the largest distance possible and involved the continuous motion; such a motion will invoke a wide range of possible nonlinear dynamic representations. The proposed control strategy is robust to variations in robot loading. The experimental results obtained for the closed-loop response indicate that compensation, which employs explicit off-line parameter estimation, can improve tracking accuracy significantly. Using the robust tracking controllers, the position errors were smaller than those obtained using the original PID controllers. The robust tracking controller showed excellent results.
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Wilson, Giles A. „Robust nonlinear control of flexible joint manipulators“. Thesis, Queen's University Belfast, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241525.
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Mills, Russell Edward. „Robust backstepping control of nonlinear uncertain systems“. Thesis, University of Sheffield, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246989.
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Dehesa, Valencia Julio César. „INTERVAL ROBUST CONTROL FOR NONLINEAR FLAT SYSTEMS“. Doctoral thesis, Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/27724.
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Esta tesis se enfoca principalmente en el control robusto de sistemas no lineales planos. El objetivo principal es determinar una familia de controladores robustos con la finalidad de asegurar el cumplimiento de un conjunto de especificaciones deseadas bajo incertidumbre paramétrica en el proceso. La familia de controladores robustos se determina con un nuevo enfoque de control robusto posibilistico conjuntamente con la teoría de los sistemas planos. Las especificaciones e incertidumbre paramétrica se establecen mediante intervalos. Se aplican la Aritmética Intervalar Modal y el Análisis de Algoritmos de Inversión de Conjuntos Cuantificados para encontrar los conjuntos de soluciones. Se resuelven diferentes problemas de control robusto tales como: Conjuntos de soluciones referidos a las especificaciones alcanzables por una familia de controladores, así como la determinación de la incertidumbre máxima admitida por un controlador nominal.
En esta tesis se desarrolla una nueva metodología de análisis de robustez de controladores basados en platitud diferencial, donde el uso de una pre alimentación es requerida. La metodología desarrollada es aplicada a diferentes procesos, específicamente a bioreactores fed-batch, dada la importancia de estos reactores de alta densidad de tanque agitado para la producción industrial eficiente de proteínas y enzimas.Dehesa Valencia, JC. (2013). INTERVAL ROBUST CONTROL FOR NONLINEAR FLAT SYSTEMS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/27724
Palancia
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SIGNORILE, MARIA CARMELA. „Robust control of nonlinear systems from data“. Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2496767.
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A general problem in the control field is to derive a model of the system to be controlled. The classical approach consists in building a mathematical model on the basis of the laws governing the system (e.g. mechanical, physical, economical) and then exploit it for de- signing a model-based control law that fulfills the desired specifications. However, such approach is not always possible for two main reasons: the uncomplete knowledge of the system laws and its nonlinearity which, respectively, do not enable to derive an accurate and tractable model. On the other hand, considering that the most of the existing sys- tems are nonlinear, the model to be derived should be a trade-off between accuracy and tractability. Indeed, the accuracy of the model, employed to design the control system, plays a crucial role since the performance achievable by the controlled system strongly depends on the size of the modeling error. In the presence of a poor accurate model, not only a performance degradation may occurr, but the closed loop stability may also be missed.
The literature of nonlinear control usually assumes that the system to be controlled and its model are well known, altough this is not always true as pointed out above. In par- ticular, the nonlinear models usually employed are neural networks or parametric models whose parameters are identified from input/output data of the process. Due to the nature of these models, does not exist a systematic procedure to obtain a suitable description of the uncertainty associated with them, which in turn hampers a systematic dealing of the robust stability.
Thus, in order to investigate the control of nonlinear and unknown systems, guaranteeing the stability of the closed loop system in the presence of model uncertainty, objective of this thesis is study the robust control of nonlinear dynamic systems from experimental data.
At this aim, a Nonlinear Set Membership (NSM) identification methodology is used to derive a data-based model. Such technique identifies a model from input/output data col- lected in previous experiments and provides a finite measure of the uncertainty associated to the model (see [1] for more details). The obtained model results to be accurate both in linear and nonlinear conditions and its accuracy can be further improved using a greater quantity of data related to several experiments performed in different conditions for its identification. Moreover, when a NSM model is employed within a control scheme, the knowledge of its uncertainty bound is fundamental to study the robust stability of the closed loop control scheme.
Among the model-based control techniques, this thesis focuses on Nonlinear Internal Model Control (NIMC) and Nonlinear Model Predictive Control (NMPC), which both require a tractable as well as accurate model also in the presence of highly nonlinear dynamics and parameter uncertainties. For this purpose, two methodologies which em- ploy a NSM model are proposed in this thesis: a Set Membership Internal Model Control (SIMC) and a Set Membership Model Predictive Control (SMPC) .
The novelty of SIMC consists in deriving the controller by cascading a filter describing the desired input/output system behavior and the inverse of the system model (see [2]). Such a novel procedure exploits the recent results on the right–inversion (see [3]) and does not require the knowledge and the invertibility of the system. This is a not negligible advantage because the inversion of nonlinear systems is not trivial and sometimes impossible. Moreover, a robust stability study shows that the obtained SIMC control structure is input/output stable with finite gain by imposing a small gain condition in the control design phase (see [4], [5]). This is the second main result proposed because usually, in literature, the stability of NIMC control loops is empirically verified a posteriori.
The SMPC methodology, instead, uses a NSM model to predict the system behavior and the its uncertainty bound to assess the robust stability of the proposed scheme (see [6]). In fact, at first, exploiting the uncertainty measure, it is shown that the SMPC control structure is robustly stable through an a posteriori stability analysis (see [7]). Then, a procedure to design a robust SMPC control law is proposed (see [8], [9]) and applied to control a nonlinear oscillator. In the case of SIMC and SMPC robust analysis, a vehicle yaw control system is designed to show the effectiveness of the proposed methodologies. A minor research theme, dealt in this thesis, is the design of robust control law using the technology of Direct Virtual Sensors (DVSs). DVSs are software algorithms derived directly from input/output data by means the NSM identification technique. They are able to estimate a variable of interest of a system exploiting some measures already avail- able [10]. It is shown that the direct identification from data implies a greater accuracy of the estimate w.r.t. the classical two steps approach (e.g. Kalman filter) [11]. Further, it is shown that using data collected in closed loop fashion allows to obtain a much accurate estimate than using open loop data [10, 11]. In this thesis, DVSs are used to develop a fault tolerant vehicle yaw control system: the DVS gets on duty and replaces the physical yaw rate sensor when a fault of the last one occurs. The DVS provides the estimate of the yaw rate which is the feedback variable guaranteeing the right working of the stability control system and hence the vehicle safety (see [12]). The novelty consists in the use of an estimated variable from experimental data for control purposes and, in particular, to replace the feedback variable. Moreover, the system in closed loop which employs the DVS results to be robustly stable through an a posteriori analysis.
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Bundell, G. A. „Robust decentralized adaptive control in the manipulator control problem“. Thesis, University of Cambridge, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.355669.
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Tjønnås, Johannes. „Nonlinear and Adaptive Dynamic Control Allocation“. Doctoral thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-2320.
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This work addresses the control allocation problem for a nonlinear over-actuated time-varying system where parameters a¢ ne in the actuator dynamics and actuator force model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. A previous result on uniform global asymptotic stability (UGAS) of the equilibrium of cascaded time-varying systems, is in the thesis shown to also hold for closed (not necessarily compact) sets composed by set-stable subsystems of a cascade. In view of this result, the optimal control allocation approach is studied by using Lyapunov analysis for cascaded set-stable systems, and uniform global/local asymptotic stability is guaranteed for the sets described by; the system dynamics, the optimizing allocation update-law and the adaptive update-law.
The performance of the proposed control allocation scheme is demon- strated throughout the thesis by simulations of a scaled-model ship manoeuvred at low-speed. Furthermore, the application of a yaw stabilization scheme for an automotive vehicle is presented. The stabilization strategy consists of; a high level module that deals with the vehicle motion control objective (yaw rate reference generation and tracking), a low level module that handles the braking control for each wheel (longitudinal slip control and maximal tyre road friction parameter estimation) and an intermediate level dynamic control allocation module. The control allocation module generates longitudinal slip reference for the low level brake controller and commands front wheel steering angle corrections, such that the actual torque about the yaw axis tends to the desired torque calculated by the high level module. The conditions for uniform asymptotic stability are given and the scheme has been implemented in a realistic nonlinear multi-body vehicle simulation environment. The simulation cases show that the control strategy stabilizes the vehicle in extreme manoeuvres where the nonlinear vehicle yaw dynamics otherwise become unstable in the sense of over- or understeering.