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Showing papers on "Robust control published in 2000"


Journal ArticleDOI
TL;DR: This paper considers problems related to stability or stabilizability of linear systems with parametric uncertainty, robust control, time-varying linear systems, nonlinear and hybrid systems, and stochastic optimal control.

785 citations


BookDOI
01 Jan 2000
TL;DR: The first € price and the £ and $ price are net prices, subject to local VAT, and the €(D) includes 7% for Germany, the€(A) includes 10% for Austria.
Abstract: The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All prices exclusive of carriage charges. Prices and other details are subject to change without notice. All errors and omissions excepted. G.E. Dullerud, F. Paganini A Course in Robust Control Theory

682 citations


Book
11 Jan 2000
TL;DR: Robust control: robust stability robust stabilization robust H-infinity control guaranteed cost control passivity analysis and synthesis interconnected systems as discussed by the authors, robust filtering: robust Kalman filtering robust Hinfinity filtering interconnected systems.
Abstract: Robust control: robust stability robust stabilization robust H-infinity control guaranteed cost control passivity analysis and synthesis interconnected systems. Robust filtering: robust Kalman filtering robust H-infinity filtering interconnected systems. Appendices: some facts from matrix theory some algebraic inequalities stability theorems positive real systems LMI control software.

645 citations


Journal ArticleDOI
TL;DR: A robust adaptive control algorithm is developed without constructing a hysteresis inverse, which ensures global stability of the adaptive system and achieves both stabilization and tracking to within a desired precision.
Abstract: Deals with adaptive control of a class of nonlinear dynamic systems preceded by unknown backlash-like hysteresis nonlinearities, where the hysteresis is modeled by a differential equation. By exploiting solution properties of the differential equation and combining those properties with adaptive control techniques, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The new control law ensures global stability of the adaptive system and achieves both stabilization and tracking to within a desired precision. Simulations performed on a nonlinear system illustrate and clarify the approach.

578 citations


Journal ArticleDOI
TL;DR: In this paper, a discontinuous projection-based adaptive robust controller (ARC) is proposed for the swing motion control of a single-rod hydraulic actuator with constant unknown inertia load, which takes into account not only the effect of parameter variations coming from the inertia load and various hydraulic parameters, but also the effects of hard to model nonlinearities such as uncompensated friction forces and external disturbances.
Abstract: High-performance robust motion control of single-rod hydraulic actuators with constant unknown inertia load is considered. The two chambers of a single-rod actuator have different areas, so the dynamic equations describing the pressure changes in them cannot be combined into a single load pressure equation. This complicates controller design since it not only increases the system dimension but also brings in the stability issue of the added internal dynamics. A discontinuous projection-based adaptive robust controller (ARC) is constructed. The controller takes into account not only the effect of parameter variations coming from the inertia load and various hydraulic parameters but also the effect of hard-to-model nonlinearities such as uncompensated friction forces and external disturbances. It guarantees a prescribed output tracking transient performance and final tracking accuracy in general while achieving asymptotic output tracking in the presence of parametric uncertainties. In addition, the zero error dynamics for tracking any nonzero constant velocity trajectory is shown to be globally uniformly stable. Experimental results are obtained for the swing motion control of a hydraulic arm and verify the high-performance nature of the proposed strategy. In comparison to a state-of-the-art industrial motion controller, the proposed algorithm achieves more than a magnitude reduction of tracking errors. Furthermore, during the constant velocity portion of the motion, it reduces the tracking errors almost down to the measurement resolution level.

559 citations


Journal ArticleDOI
TL;DR: An adaptive output feedback control scheme for the output tracking of a class of continuous-time nonlinear plants is presented and it is shown that by using adaptive control in conjunction with robust control, it is possible to tolerate larger approximation errors resulting from the use of lower order networks.
Abstract: An adaptive output feedback control scheme for the output tracking of a class of continuous-time nonlinear plants is presented. An RBF neural network is used to adaptively compensate for the plant nonlinearities. The network weights are adapted using a Lyapunov-based design. The method uses parameter projection, control saturation, and a high-gain observer to achieve semi-global uniform ultimate boundedness. The effectiveness of the proposed method is demonstrated through simulations. The simulations also show that by using adaptive control in conjunction with robust control, it is possible to tolerate larger approximation errors resulting from the use of lower order networks.

529 citations


BookDOI
01 Jan 2000
TL;DR: In this paper, the authors considered the problem of guaranteed cost control for uncertain linear systems with additive noise. But they did not consider the nonlinearity of uncertain systems with integral quadratic constraints.
Abstract: 1. Introduction.- 1.1 The concept of an uncertain system.- 1.2 Overview of the book.- 2. Uncertain systems.- 2.1 Introduction.- 2.2 Uncertain systems with norm-bounded uncertainty.- 2.2.1 Special case: sector-bounded nonlinearities.- 2.3 Uncertain systems with integral quadratic constraints.- 2.3.1 Integral quadratic constraints.- 2.3.2 Integral quadratic constraints with weighting coefficients.- 2.3.3 Integral uncertainty constraints for nonlinear uncertain systems.- 2.3.4 Averaged integral uncertainty constraints.- 2.4 Stochastic uncertain systems.- 2.4.1 Stochastic uncertain systems with multiplicative noise.- 2.4.2 Stochastic uncertain systems with additive noise: Finitehorizon relative entropy constraints.- 2.4.3 Stochastic uncertain systems with additive noise: Infinite-horizon relative entropy constraints.- 3. H? control and related preliminary results.- 3.1 Riccati equations.- 3.2 H? control.- 3.2.1 The standard H? control problem.- 3.2.2 H? control with transients.- 3.2.3 H? control of time-varying systems.- 3.3 Risk-sensitive control.- 3.3.1 Exponential-of-integral cost analysis.- 3.3.2 Finite-horizon risk-sensitive control.- 3.3.3 Infinite-horizon risk-sensitive control.- 3.4 Quadratic stability.- 3.5 A connection between H? control and the absolute stabilizability of uncertain systems.- 3.5.1 Definitions.- 3.5.2 The equivalence between absolute stabilization and H? control.- 4. The S-procedure.- 4.1 Introduction.- 4.2 An S-procedure result for a quadratic functional and one quadratic constraint.- 4.2.1 Proof of Theorem 4.2.1.- 4.3 An S-procedure result for a quadratic functional and k quadratic constraints.- 4.4 An S-procedure result for nonlinear functionals.- 4.5 An S-procedure result for averaged sequences.- 4.6 An S-procedure result for probability measures with constrained relative entropies.- 5. Guaranteed cost control of time-invariant uncertain systems.- 5.1 Introduction.- 5.2 Optimal guaranteed cost control for uncertain linear systems with norm-bounded uncertainty.- 5.2.1 Quadratic guaranteed cost control.- 5.2.2 Optimal controller design.- 5.2.3 Illustrative example.- 5.3 State-feedback minimax optimal control of uncertain systems with structured uncertainty.- 5.3.1 Definitions.- 5.3.2 Construction of a guaranteed cost controller.- 5.3.3 Illustrative example.- 5.4 Output-feedback minimax optimal control of uncertain systems with unstructured uncertainty.- 5.4.1 Definitions.- 5.4.2 A necessary and sufficient condition for guaranteed cost stabilizability.- 5.4.3 Optimizing the guaranteed cost bound.- 5.4.4 Illustrative example.- 5.5 Guaranteed cost control via a Lyapunov function of the Lur'e-Postnikov form.- 5.5.1 Problem formulation.- 5.5.2 Controller synthesis via a Lyapunov function of the Lur'e-Postnikov form.- 5.5.3 Illustrative Example.- 5.6 Conclusions.- 6. Finite-horizon guaranteed cost control.- 6.1 Introduction.- 6.2 The uncertainty averaging approach to state-feedback minimax optimal control.- 6.2.1 Problem Statement.- 6.2.2 A necessary and sufficient condition for the existence of a state-feedback guaranteed cost controller.- 6.3 The uncertainty averaging approach to output-feedback optimal guaranteed cost control.- 6.3.1 Problem statement.- 6.3.2 A necessary and sufficient condition for the existence of a guaranteed cost controller.- 6.4 Robust control with a terminal state constraint.- 6.4.1 Problem Statement.- 6.4.2 A criterion for robust controllability with respect to a terminal state constraint.- 6.4.3 Illustrative example.- 6.5 Robust control with rejection of harmonic disturbances.- 6.5.1 Problem Statement.- 6.5.2 Design of a robust controller with harmonic disturbance rejection.- 6.6 Conclusions.- 7. Absolute stability, absolute stabilization and structured dissipativity.- 7.1 Introduction.- 7.2 Robust stabilization with a Lyapunov function of the Lur'e-Postnikov form.- 7.2.1 Problem statement.- 7.2.2 Design of a robustly stabilizing controller.- 7.3 Structured dissipativity and absolute stability for nonlinear uncertain systems.- 7.3.1 Preliminary remarks.- 7.3.2 Definitions.- 7.3.3 A connection between dissipativity and structured dissipativity.- 7.3.4 Absolute stability for nonlinear uncertain systems.- 7.4 Conclusions.- 8. Robust control of stochastic uncertain systems.- 8.1 Introduction.- 8.2 H? control of stochastic systems with multiplicative noise.- 8.2.1 A stochastic differential game.- 8.2.2 Stochastic H? control with complete state measurements.- 8.2.3 Illustrative example.- 8.3 Absolute stabilization and minimax optimal control of stochastic uncertain systems with multiplicative noise.- 8.3.1 The stochastic guaranteed cost control problem.- 8.3.2 Stochastic absolute stabilization.- 8.3.3 State-feedback minimax optimal control.- 8.4 Output-feedback finite-horizon minimax optimal control of stochastic uncertain systems with additive noise.- 8.4.1 Definitions.- 8.4.2 Finite-horizon minimax optimal control with stochastic uncertainty constraints.- 8.4.3 Design of a finite-horizon minimax optimal controller.- 8.5 Output-feedback infinite-horizon minimax optimal control of stochastic uncertain systems with additive noise.- 8.5.1 Definitions.- 8.5.2 Absolute stability and absolute stabilizability.- 8.5.3 A connection between risk-sensitive optimal control and minimax optimal control.- 8.5.4 Design of the infinite-horizon minimax optimal controller.- 8.5.5 Connection to H? control.- 8.5.6 Illustrative example.- 8.6 Conclusions.- 9. Nonlinear versus linear control.- 9.1 Introduction.- 9.2 Nonlinear versus linear control in the absolute stabilizability of uncertain systems with structured uncertainty.- 9.2.1 Problem statement.- 9.2.2 Output-feedback nonlinear versus linear control.- 9.2.3 State-feedback nonlinear versus linear control.- 9.3 Decentralized robust state-feedback H? control for uncertain large-scale systems.- 9.3.1 Preliminary remarks.- 9.3.2 Uncertain large-scale systems.- 9.3.3 Decentralized controller design.- 9.4 Nonlinear versus linear control in the robust stabilizability of linear uncertain systems via a fixed-order output-feedback controller.- 9.4.1 Definitions.- 9.4.2 Design of a fixed-order output-feedback controller.- 9.5 Simultaneous H? control of a finite collection of linear plants with a single nonlinear digital controller.- 9.5.1 Problem statement.- 9.5.2 The design of a digital output-feedback controller.- 9.6 Conclusions.- 10. Missile autopilot design via minimax optimal control of stochastic uncertain systems.- 10.1 Introduction.- 10.2 Missile autopilot model.- 10.2.1 Uncertain system model.- 10.3 Robust controller design.- 10.3.1 State-feedback controller design.- 10.3.2 Output-feedback controller design.- 10.4 Conclusions.- 11. Robust control of acoustic noise in a duct via minimax optimal LQG control.- 11.1 Introduction.- 11.2 Experimental setup and modeling.- 11.2.1 Experimental setup.- 11.2.2 System identification and nominal modelling.- 11.2.3 Uncertainty modelling.- 11.3 Controller design.- 11.4 Experimental results.- 11.5 Conclusions.- A. Basic duality relationships for relative entropy.- B. Metrically transitive transformations.- References.

485 citations


Journal ArticleDOI
TL;DR: This study introduces a mixed H/sub 2//H/sub /spl infin// fuzzy output feedback control design method for nonlinear systems with guaranteed control performance using the Takagi-Sugeno fuzzy model to approximate a nonlinear system.
Abstract: This study introduces a mixed H/sub 2//H/sub /spl infin// fuzzy output feedback control design method for nonlinear systems with guaranteed control performance. First, the Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system. Next, based on the fuzzy model, a fuzzy observer-based mixed H/sub 2//H/sub /spl infin// controller is developed to achieve the suboptimal H/sub 2/ control performance with a desired H/sub /spl infin// disturbance rejection constraint. A robust stabilization technique is also proposed to override the effect of approximation error in the fuzzy approximation procedure. By the proposed decoupling technique and two-stage procedure, the outcome of the fuzzy observer-based mixed H/sub 2//H/sub /spl infin// control problem is parametrized in terms of the two eigenvalue problems (EVPs): one for observer and the other for controller. The EVPs can be solved very efficiently using the linear matrix inequality (LMI) optimization techniques. A simulation example is given to illustrate the design procedures and performances of the proposed method.

454 citations


Journal ArticleDOI
TL;DR: It is shown that, within the framework of the quadratic-criterion-based ILC (Q-ILC), various practical issues such as constraints, disturbances, measurement noises, and model errors can be considered in a rigorous and systematic manner.

451 citations


BookDOI
01 Jan 2000
TL;DR: A linear matrix inequality approach to the design of Robust H2 Filters and applications:Linear Controller Design for the NEC Laser Bonder via Linear Matrix Inequality Optimization and Applications.
Abstract: Preface Notation Part I. Introduction. Robust Decision Problems in Engineering: A linear matrix inequality approach L. El Ghaoui and S.-I. Niculescu Part II. Algorithms and Software: Mixed Semidefinite-Quadratic-Linear Programs J.-P. A. Haeberly, M. V. Nayakkankuppam and M. L. Overton Nonsmooth algorithms to solve semidefinite programs C. Lemarechal and F. Oustry sdpsol: A Parser/Solver for Semidefinite Programs with Matrix Structure S.-P. Wu and S. Boyd Part III. Analysis: Parametric Lyapunov Functions for Uncertain Systems: The Multiplier Approach M. Fu and S. Dasgupta Optimization of Integral Quadratic Constraints U. Jonsson and A. Rantzer Linear Matrix Inequality Methods for Robust H2 Analysis: A Survey with Comparisons F. Paganini and E. Feron Part IV. Synthesis. Robust H2 Control K. Y. Yang, S. R. Hall and E. Feron Linear Matrix Inequality Approach to the Design of Robust H2 Filters C. E. de Souza and A. Trofino Robust Mixed Control and Linear Parameter-Varying Control with Full Block Scalings C. W. Scherer Advanced Gain-Scheduling Techniques for Uncertain Systems P. Apkarian and R. J. Adams Control Synthesis for Well-Posedness of Feedback Systems T. Iwasaki Part V. Nonconvex Problems. Alternating Projection Algorithms for Linear Matrix Inequalities Problems with Rank Constraints K. M. Grigoriadis and E. B. Beran Bilinearity and Complementarity in Robust Control M. Mesbahi, M. G. Safonov and G. P. Papavassilopoulos Part VI. Applications:Linear Controller Design for the NEC Laser Bonder via Linear Matrix Inequality Optimization J. Oishi and V. Balakrishnan Multiobjective Robust Control Toolbox for LMI-Based Control S. Dussy Multiobjective Control for Robot Telemanipulators J. P. Folcher and C. Andriot Bibliography Index.

435 citations


Journal ArticleDOI
01 Nov 2000
TL;DR: A controller is proposed for the robust backstepping control of a class of general nonlinear systems using neural networks (NNs) and can guarantee the boundedness of tracking error and weight updates.
Abstract: A controller is proposed for the robust backstepping control of a class of general nonlinear systems using neural networks (NNs). A tuning scheme is proposed which can guarantee the boundedness of tracking error and weight updates. Compared with adaptive backstepping control schemes, we do not require the unknown parameters to be linear parametrizable. No regression matrices are needed, so no preliminary dynamical analysis is needed. One salient feature of our NN approach is that there is no need for the off-line learning phase. Three nonlinear systems, including a one-link robot, an induction motor, and a rigid-link flexible-joint robot, were used to demonstrate the effectiveness of the proposed scheme.

Journal ArticleDOI
TL;DR: This work proposes an approach that deploys a fixed state-feedback law but introduces extra degrees of freedom through the use of perturbations on the fixedState-Feedback law to allow for better performance and wider applicability.
Abstract: Predictive constrained control of time-varying and/or uncertain linear systems has been effected through the use of ellipsoidal invariant sets (Kothare et al., 1996). Linear matrix inequalities (LMIs) have been used to design a state-dependent state-feedback law that maintains the state vector inside invariant feasible sets. For the purposes of prediction however, at each time instant, the state feedback law is assumed constant. In addition, due to the large number of LMIs involved, online computation becomes intractable for anything other than small dimensional systems. Here we propose an approach that deploys a fixed state-feedback law but introduces extra degrees of freedom through the use of perturbations on the fixed state-feedback law. The problem is so formulated that all demanding computations can be performed offline leaving only a simple optimization problem to be solved online. Over and above the very significant reduction in computational cost, the extra degrees of freedom allow for better performance and wider applicability.

Journal ArticleDOI
TL;DR: In this paper, the robust stochastic stabilizability and robust H/sub /spl infin// disturbance attenuation for a class of uncertain linear systems with time delay and randomly jumping parameters are investigated.
Abstract: This paper is concerned with the robust stochastic stabilizability and robust H/sub /spl infin// disturbance attenuation for a class of uncertain linear systems with time delay and randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. Sufficient conditions on the existence of a robust stochastic stabilizing and /spl gamma/-suboptimal H/sub /spl infin// state-feedback controller are presented using the Lyapunov functional approach. It is shown that a robust stochastically stabilizing H/sub /spl infin// state-feedback controller can be constructed through the numerical solution of a set of coupled linear matrix inequalities.

Proceedings ArticleDOI
01 Dec 2000
TL;DR: In this paper, the authors propose a control architecture based on a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle, in the presence of disturbances and uncertainties in the plant and/or in the environment.
Abstract: The operation of an autonomous vehicle in an unknown, dynamic environment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities, and to react in real time to changes in the operational environment. A possible approach to reduce the computational complexity of the motion planning problem for a nonlinear, high dimensional system, is based on a quantization of the system dynamics, leading to a control architecture based on a hybrid automaton, the states of which represent feasible trajectory primitives for the vehicle. The paper focuses on the feasibility of this approach, in the presence of disturbances and uncertainties in the plant and/or in the environment: the structure of a robust hybrid automaton is defined and its properties are analyzed. In particular, we address the issues of well-posedness, consistency and reachability. For the case of autonomous vehicles, we provide sufficient conditions to guarantee reachability of the automaton.

Journal ArticleDOI
TL;DR: In this paper, a robust H∞ controller was developed to deliver insulin via a mechanical pump in Type I diabetic patients, and the controller was evaluated in terms of its ability to track a normoglycemic set point (81.1 mg/dL) in response to a 50 g meal disturbance.
Abstract: A robust H∞ controller was developed to deliver insulin via a mechanical pump in Type I diabetic patients. A fundamental nonlinear diabetic patient model was linearized and then reduced to a third-order linear form for controller synthesis. Uncertainty in the nonlinear model was characterized by up to ± 40% variation in eight physiological parameters. A sensitivity analysis identified the three-parameter set having the most significant effect on glucose and insulin dynamics over the frequency range of interest ω = [0.002, 0.2] (rad/min). This uncertainty was represented in the frequency domain and incorporated in the controller design. Controller performance was assessed in terms of its ability to track a normoglycemic set point (81.1 mg/dL) in response to a 50 g meal disturbance. In the nominal continuous-time case, the controller maintained glucose concentrations within ± 3.3 mg/dL of set point. A controller tuned to accommodate uncertainty yielded a maximum deviation of 17.6 mg/dL for the worst-case parameter variation.

Journal ArticleDOI
TL;DR: A control design method for diesel engines equipped with a variable geometry turbocharger and an exhaust gas recirculation valve that possesses a guaranteed robustness property equivalent to gain and phase margins is presented.
Abstract: Presents a control design method for diesel engines equipped with a variable geometry turbocharger and an exhaust gas recirculation valve. Our control objective is to regulate the air-fuel ratio and the fraction of recirculated exhaust gas to their respective set points that depend on engine operating conditions. Interactions between the two actuators and nonlinear behavior of the system make the problem difficult to handle using classical control design methods. Instead, we employ a control Lyapunov function (CLF) based nonlinear control design method because it possesses a guaranteed robustness property equivalent to gain and phase margins. The CLF is constructed using input-output linearization of a reduced order diesel engine model. The controller has been tested in simulations on the full order model as well as experimentally in the dynamometer test cell.

Journal ArticleDOI
TL;DR: In this article, the authors present the second edition of a textbook published in 1996 by McGraw Hill and originates from a graduate level course given by the authors at the University of Naples.
Abstract: This book is the second edition of a textbook published in 1996 by McGraw Hill and originates from a graduate level course given by the authors at the University of Naples. The topics include kinematics, statics and dynamics of robot manipulators together with trajectory planning and active control. There are only minor additions the first edition, which are mainly the use of quaternion to describe the orientation of the end effector and a short description of a closed chain architecture for a manipulator (parallelogram arm). The book is largely devoted to serial manipulators, with special developments about active control including adaptative control, robust controls and stability analysis. Another strength of this book is the great number of problems proposed at the end of each chapter, together with a list of references related to it. The fundamental features covered by the text are illustrated on simple examples of serial manipulators (two-link planar arm, parallelogram arm) including analytical results and numerical tests. The book has nine chapters followed by three appendices. The first appendix is devoted to linear algebra, the second recalls some fundamental aspects of rigid body mechanics and the third gives some basic principles of feedback control of linear systems. Chapter one is an introduction to the study of robot manipulators, giving an interesting classification of their architectures, the corresponding workspace and describes the tasks for which they are used. After some standard examples of industrial manipulators, bibliographical reference texts are proposed, including textbooks on modelling and control of robots, general books on robotics, specialized texts, scientific robotic reviews and some international conferences on robotics. Chapters two, three and four are devoted to mechanical modelling of robot manipulators. The fundamental basics of kinematics are given in chapter two, including the representation of finite rotations by Euler angles or unit quaternions, homogeneous transformations, Denavit-Hartenberg parameters and workspace. The direct and inverse kinematical problems are solved in analytical form for some typical manipulator structures. The differential kinematics of robots are presented in chapter three, with an introduction to the geometric and analytic Jacobian matrices, kinematic singularities and redundancy. The inverse kinematic problem is presented, with special attention to the case of redundant robots where the solution is obtained by a linear optimization problem leading to the introduction of the pseudo-inverse Jacobian matrix and to the solution of several objectives such as avoidance of collision with an obstacle or moving away from singularities. Several inverse kinematics algorithms are given wih an interesting application to a three-link planar arm. Finally, a property of kineto-statics duality is deduced from the principle of virtual work applied to an equilibrium configuration of the robot. Chapter four is a standard presentation of the derivation of the dynamical model by Lagrange formulation and then by the Newton-Euler method. In the Lagrange formulation method, the linearity with respect to inertial parameters is shown and a detailed formulation of the dynamical model is obtained for a two-link Cartesian arm, a two-link planar arm and a parallelogram arm. The problem of dynamic parameter identification is also briefly presented from a numerical point of view. The recursive algorithm constructed from the Newton-Euler formulation is presented and illustrated by considering a two-link planar arm. Finally, the operational space dynamic model is introduced. In chapter five, paths and trajectory planning in joints and in operational spaces are presented; several classical methods of interpolation are described. Chapter six is an extensive study of active control of manipulators. Several methods are presented, involving classical independent joint control, non-linear centralized control, robust control and adaptative control. Both joint-space control and operational-space control are studied together with stability analysis by using Liapounoff functions. An interesting application to the two-link planar arm already used shows the comparison between various control schemes. Chapter seven deals with interaction control of serial manipulators with the working environment. Several strategies involving compliance control, impedance control, force control and hybrid control are presented. Chapter eight describes the actuators and the sensors used in robotics. Several types of servomotors (electric and hydraulic) are presented, together with the model giving their input/output relationship. Several kinds of sensors are also described including encoders, tachometers, force and vision sensors. The last chapter gives a short presentation of the functional architecture of a robot's control system, including characteristics of the programing environment and the hardware architecture. In conclusion, the book provides a good insight about simulation and control of robot manipulators, with a detailed study of the various control strategies and several interesting and pedagogical applications. This book is an excellent review of the standard knowledge needed not only for graduate students but also for researchers interested in robot manipulators. M Pascal

Journal ArticleDOI
TL;DR: In this article, a fast voltage control strategy of three-phase AC/DC pulsewidth modulation (PWM) converters applying a feedback linearization technique is proposed, and the experimental results are provided to verify the validity of the proposed control algorithm for a 1.5 kVA insulated gate bipolar transistor PWM converter system.
Abstract: In this paper, a fast voltage control strategy of three-phase AC/DC pulsewidth modulation (PWM) converters applying a feedback linearization technique is proposed. First, incorporating the power balance of the input and output sides in system modeling, a nonlinear model of the PWM converter is derived with state variables such as AC input currents and DC output voltage. Then, by input-output feedback linearization, the system is linearized and a state feedback control law is obtained by pole placement. With this control scheme, output voltage responses become faster than those in a conventional cascade control structure. For robust control to parameter variations, integrators are added to the exact feedback control law. Since the fast voltage control is feasible for load changes, it is shown that the DC electrolytic capacitor size can be reduced. In addition, the capacitor current is analyzed for size reduction of the capacitor. As is usual with PWM converters, the input current is regulated to be sinusoidal and the source power factor can be controlled at unity. The experimental results are provided to verify the validity of the proposed control algorithm for a 1.5 kVA insulated gate bipolar transistor PWM converter system.

Journal ArticleDOI
TL;DR: This paper describes an application of nonlinear decentralized robust control (Guo, Jiang & Hill, 1998) to large-scale power systems and uses nonlinear bounds of generator interconnections to achieve less-conservative control gains.

Journal ArticleDOI
TL;DR: Two kinds of adaptive control schemes for robot manipulator which has the parametric uncertainties are presented and the proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance.
Abstract: This paper presents two kinds of adaptive control schemes for robot manipulator which has the parametric uncertainties. In order to compensate these uncertainties, we use the FLS (fuzzy logic system) that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tune the parameters. We also suggest the robust adaptive control laws in all proposed schemes for decreasing the effect of approximation error. To reduce the number of fuzzy rules of the FLS, we consider the properties of robot dynamics and the decomposition of the uncertainty function. The proposed controllers are robust not only to the structured uncertainty such as payload parameter, but also to the unstructured one such as friction model and disturbance. The validity of the control scheme is shown by computer simulations of a two-link planar robot manipulator.

Journal ArticleDOI
TL;DR: This paper solves problems of worst-case robust performance analysis and output feedback minimax optimal controller synthesis in a general nonlinear setting and shows that the minimax LQG problem will have a solution if and only if a corresponding H/sup /spl infin// control problem has a solution.
Abstract: This paper considers a new class of discrete time stochastic uncertain systems in which the uncertainty is described by a constraint on the relative entropy between a nominal noise distribution and the perturbed noise distribution. This uncertainty description is a natural extension to the case of stochastic uncertain systems, of the sum quadratic constraint uncertainty description. This paper solves problems of worst-case robust performance analysis and output feedback minimax optimal controller synthesis in a general nonlinear setting. Specializing these results to the linear case leads to a minimax linear quadratic Gaussian (LQG) optimal controller. This controller is defined by Riccati difference equations and a Kalman filter-like state equation. The paper also shows that the minimax LQG problem will have a solution if and only if a corresponding H/sup /spl infin// control problem has a solution. A linear example is presented to illustrate the minimax LQG methodology.

Journal ArticleDOI
TL;DR: A digital signal processor (DSP)-based robust nonlinear speed control of a permanent magnet synchronous motor (PMSM) is presented and a boundary layer integral sliding mode controller is designed and compared to a feedback linearization-based controller.
Abstract: A digital signal processor (DSP)-based robust nonlinear speed control of a permanent magnet synchronous motor (PMSM) is presented. A quasi-linearized and decoupled model including the influence of parameter variations and speed measurement error on the input-output feedback linearization of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller is designed and compared to a feedback linearization-based controller that uses proportional plus derivative (PD) controller in the outer loop. To show the validity of the proposed control scheme, DSP-based experimental works are carried out and compared with the conventional control scheme.

Proceedings ArticleDOI
08 Oct 2000
TL;DR: In this paper, a fuzzy logic speed controller is employed in the outer loop of an IM drive for speed control of an induction motor using indirect vector control, and the performance of the proposed FLC based IM drive is compared to those obtained from the conventional proportional integral (PI) controller based drive both theoretically and experimentally at different dynamic operating conditions such as sudden change in command speed, step change in load, etc.
Abstract: This paper presents a novel speed control scheme of an induction motor (IM) using fuzzy logic control. The fuzzy logic controller (FLC) is based on the indirect vector control. The fuzzy logic speed controller is employed in the outer loop. The complete vector control scheme of the IM drive incorporating the FLC is experimentally implemented using a digital signal processor board DS-1102 for the laboratory 1 hp squirrel cage induction motor. The performances of the proposed FLC based IM drive are investigated and compared to those obtained from the conventional proportional integral (PI) controller based drive both theoretically and experimentally at different dynamic operating conditions such as sudden change in command speed, step change in load, etc. The comparative experimental results show that the FLC is more robust and hence found to be a suitable replacement of the conventional PI controller for the high performance industrial drive applications.

Journal ArticleDOI
TL;DR: A circular chain control (3C) strategy for inverters in parallel operation is presented in the paper to reach the robustness of the multimodule inverter system and to reduce possible interactive effects among inverters.
Abstract: A circular chain control (3C) strategy for inverters in parallel operation is presented in the paper. In the proposed inverter system, all the modules have the same circuit configuration, and each module includes an inner current loop and an outer voltage loop control. A proportional-integral controller is adopted as the inner current loop controller to expedite the dynamic response, while an H/sup /spl infin// robust controller is adopted to reach the robustness of the multimodule inverter system and to reduce possible interactive effects among inverters. With the 3C strategy, the modules are in circular chain connection and each module has an inner current loop control to track the inductor current of its previous module, achieving an equal current distribution. Simulation results of two-module and a three-module inverter systems with different kinds of loads and with modular discrepancy have demonstrated the feasibility of the proposed control scheme. Hardware measurements are also presented to verify the theoretical discussion.

Journal ArticleDOI
TL;DR: An iterative procedure of constructing a stabilizing controller using appropriate Lynapunov-Krasovskii functionals is developed and a practical industry process is provided to illustrate the application of the main result.
Abstract: This paper examines the problem of robust stabilization of a class of triangular structural time-delay nonlinear systems. Based on the constructive use of appropriate Lynapunov-Krasovskii functionals, an iterative procedure of constructing a stabilizing controller is developed. A practical industry process is provided to illustrate the application of the main result.

Journal ArticleDOI
Yingmin Jia1
TL;DR: A nonlinear vehicle model is developed which both takes the acceleration and braking effects on the system dynamics into account and avoids using the complicated side force relation, and a robust control scheme is proposed.
Abstract: This paper mainly studies robust steering and traction of four-wheel steering (4WS) vehicles with varying velocity, mass, moment of inertia, and road-tire interaction. To this end, a nonlinear vehicle model is developed which both takes the acceleration and braking effects on the system dynamics into account and avoids using the complicated side force relation. Based on this model, a nonlinear input-output decoupling controller is first designed, by which the vehicle system can be decoupled into three two-order subsystems, i.e., the velocity subsystem controlled by the longitudinal acceleration/braking force, the lateral motion subsystem by the front steering angle, and the yaw motion subsystem by the rear steering angle, so that the load of the driver can be relieved. Especially, a new decoupling condition is derived. It is proved that a vehicle with the front wheel braking or rear wheel drive can always be decoupled provided it does not accelerate so fast or brake so hard that its front or rear wheels are lifted from the ground. Furthermore, in order to reduce the effects of the vehicle parameter variations on steering performance, a robust control scheme is proposed. The corresponding controller and observer gains can be obtained by solving two new Riccati algebraic equations. Meanwhile, by properly choosing the form of the observer, the robust controller does not destroy the decoupling structure of the longitudinal and yaw motions. The numerical simulation shows that the robust control with decoupling performance can improve safety and comfort of the vehicle driving.

Journal ArticleDOI
TL;DR: In this article, an output feedback robust H/sup /spl infin// control problem for a class of uncertain fuzzy dynamic systems with time-varying delayed state is presented.
Abstract: This paper presents an output feedback robust H/sup /spl infin// control problem for a class of uncertain fuzzy dynamic systems with time-varying delayed state. The Takagi-Sugeno fuzzy model is employed to represent an uncertain nonlinear systems with time-varying delayed state. Using a single quadratic Lyapunov function, the globally exponential stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H/sup /spl infin// controllers are given in terms of matrix inequalities. Constructive algorithm for design of robust H/sup /spl infin// controller is also developed. The resulting controller is nonlinear and automatically tuned based on fuzzy operation.

Journal ArticleDOI
TL;DR: This paper proposes a sufficient condition on robust stability of the fuzzy models and some sufficient conditions are derived on robust -disturbance attenuation in which both robust stability and a prescribed performance are required to be achieved, irrespective of the uncertainties.
Abstract: The paper is concerned with robust stabilization and H/sub /spl infin// control of a class of uncertain discrete-time fuzzy systems. The class of uncertain systems is described by state space Takagi-Sugeno (TS) fuzzy models with linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. First, a sufficient condition on robust stability of the fuzzy models is proposed. Then, H/sub /spl infin//-disturbance attenuation performance of the fuzzy models is analyzed. Some sufficient conditions are derived on robust H/sub /spl infin//-disturbance attenuation in which both robust stability and a prescribed H/sub /spl infin// performance are required to be achieved, irrespective of the uncertainties. A numerical example shows the use of the results on the stabilization and H/sub /spl infin//-disturbance attenuation of a class of discrete-time nonlinear systems via fuzzy switch.

Proceedings ArticleDOI
28 Jun 2000
TL;DR: A stabilizing controller is obtained by designing a model predictive controller, which is based on the minimization of a weighted l/sub 1///spl infin/-norm of the tracking error and the input trajectories over a finite horizon.
Abstract: We propose a procedure for synthesizing piecewise linear optimal controllers for discrete-time hybrid systems. A stabilizing controller is obtained by designing a model predictive controller, which is based on the minimization of a weighted l/sub 1///spl infin/-norm of the tracking error and the input trajectories over a finite horizon. The control law is obtained by solving a multiparametric mixed-integer linear program, which avoids solving mixed-integer programs online. As the resulting control law is piecewise affine, online computation is drastically reduced to a simple linear function evaluation.

Journal ArticleDOI
TL;DR: In the space of unknown nonlinear functions, the generalized Lipschitz norm is a suitable measure for characterizing the size of the structure uncertainty, and that the maximum uncertainty that can be dealt with by the feedback mechanism is described by a ball with radius 3/2+/spl radic/2 in this normed function space.
Abstract: Feedback is used primarily for reducing the effects of the plant uncertainty on the performance of control systems, and as such understanding the following questions is of fundamental importance: How much uncertainty can be dealt with by feedback? What are the limitations of feedback? How does the feedback performance depend quantitatively on the system uncertainty? How can the capability of feedback be enhanced if a priori information about the system structure is available? As a starting point toward answering these questions, a typical class of first-order discrete-time dynamical control systems with both unknown nonlinear structure and unknown disturbances is selected for our investigation, and some concrete answers are obtained in the paper. In particular, we find that in the space of unknown nonlinear functions, the generalized Lipschitz norm is a suitable measure for characterizing the size of the structure uncertainty, and that the maximum uncertainty that can be dealt with by the feedback mechanism is described by a ball with radius 3/2+/spl radic/2 in this normed function space.