Suitable either as a reference for practicing engineers or as a text for a graduate course in adaptive control systems, this book is a self -contained compendium of readily implementable adaptive control algorithms that have been developed and applied by the authors for over fifteen years. These algorithms, which do not require the user to identify the process parameters explicitly, have been successfully applied to a wide variety of engineering problems including flexible structure control, blood pressure control, and robotics; they are suitable for a wide variety of multiple input-output…mehr
Suitable either as a reference for practicing engineers or as a text for a graduate course in adaptive control systems, this book is a self -contained compendium of readily implementable adaptive control algorithms that have been developed and applied by the authors for over fifteen years. These algorithms, which do not require the user to identify the process parameters explicitly, have been successfully applied to a wide variety of engineering problems including flexible structure control, blood pressure control, and robotics; they are suitable for a wide variety of multiple input-output control systems with uncertainity and external disturbances. The text is intended to enable anyone with knowledge of basic linear multivariable systems to adapt the algorithms to problems in a wide variety of disciplines. Thus, in addition to developing the theoretical details of the algorithms presented, the text gives considerable emphasis to design of algorithms and to representative applications in flight control, flexible structure control, robotics, and drug-infusion control. Engineers can thus use and test these algorithms in practical problems. This second edition has been corrected and updated throughout. It makes use of MATLAB programs for some of the illustrative examples; these programs are described in the text and can be obtained from the MathWorks file server.
Suitable either as a reference or as a graduate-level text in adaptive control systems, the text is a self-contained compendium of adaptive control algorithms readily implementable with regard to a wide variety of engineering problems, developed and applied by the authors for over fifteen years. Corrected and updated throughout, the second edition also includes a diskette with MATLAB programs to run some of the illustrative examples.
Inhaltsangabe
1 Introduction.- 1.1 Definition of the Problem.- 1.2 Prologue to Simple Adaptive Control.- 1.3 Background on Adaptive Control Algorithms.- 1.4 Objectives and Overview.- 1.5 Software Availability for Example Problems.- 2 Basic Theory of Simple Adaptive Control.- 2.1 Model Following.- 2.2 Output Model Following.- 2.3 Stability and Positivity Concepts.- 2.4 Adaptive Control Based on CGT.- 2.5 The Adaptive Algorithm with General Input Commands.- 2.6 Summary of Adaptive Algorithms.- Appendix 2A Proof of Theorem 2.1.- Appendix 2B Proof of Theorem 2.2.- Appendix 2C Poles, Zeros, and Relative Degree in Multivariable Systems.- 3 Extensions of the Basic Adaptive Algorithm.- 3.1 Parallel Feedforward and Stability Considerations.- 3.2 Feedforward Around Plant.- 3.3 Feedforward in Both Plant and Model.- 3.4 A Unified Approach to Supplementary Dynamics.- 3.5 Adaptive Control in the Presence of Nonlinearities.- 3.6 Summary.- Appendix 3A Proof of Positivity Lemmas.- Appendix 3B Proof of Theorem 3.1.- Appendix 3C Proof of Theorem 3.2.- Appendix 3D Proof of Theorem 3.3.- Appendix 3E Proof of Theorem 3.4.- Appendix 3F Outline of Proof of Theorem 3.5.- 4 Robust Design Procedures.- 4.1 Introduction.- 4.2 Robust Redesign of the Basic Adaptive Algorithm.- 4.3 Robustness Considerations with Feedforward in the Reference Model.- 4.4 Robust Redesign for Supplementary Dynamics.- 4.5 Bursting Phenomena and Their Elimination.- 4.6 Summary.- Appendix 4A Proof of Robust Stability, Theorem 4.1.- Appendix 4B Development of Lyapunov Function Derivative.- Appendix 4C Proof of Theorem 4.2.- 5 Adaptive Control of Time-Varying and Nonlinear Systems.- 5.1 Introduction.- 5.2 Passivity and Almost Passivity of Nonstationary Systems.- 5.3 Adaptive Control of ASP Plants.- 5.4 The "Almost Passivity" Lemmas.-5.5 Passivity and Almost Passivity of Nonlinear Systems.- 5.6 Simple Adaptive Control for a Class of Nonlinear Systems.- 5.7 Simple Adaptive Control of Rigid Robotic Manipulators.- 5.8 Summary.- Appendix 5A Proof of Stability for the Algorithm (5.27)-(5.32).- Appendix 5B Strictly Causal Almost Passive Systems.- Appendix 5C Proof of Lemma 5.1.- Appendix 5D Proof of Almost Passivity Lemma in Nonlinear Systems.- Appendix 5E Almost Passivity with Application to Manipulators.- Appendix 5F The Proof of Stability of the Adaptive Control Algorithm.- Appendix 5G Adaptive Control of Strictly Causal Almost Passive Systems.- 6 Design of Model Reference Adaptive Controllers.- 6.1 Algorithm Overview.- 6.2 Constraint Satisfaction.- 6.3 Weight Selection.- 6.4 Reference Model Selection.- 6.5 Digital Implementation.- 6.6 Time-Varying Commands.- Appendix 6A Proof of Theorem 6.1.- Appendix 6B Proof of Theorem 6.2.- Appendix 6C Proof of Lemma 6.1.- Appendix 6D Proof of Theorem 6.3.- 7 Case Studies.- 7.1 Direct Model Reference Adaptive Control of a PUMA Manipulator.- 7.2 Model Reference Adaptive Control of Large Structures.- 7.3 Adaptive Drug Delivery Control.- 7.4 Adaptive Control for a Relaxed Static Stability Aircraft.- 7.5 Liquid Level System Emulation.- References.
1 Introduction.- 1.1 Definition of the Problem.- 1.2 Prologue to Simple Adaptive Control.- 1.3 Background on Adaptive Control Algorithms.- 1.4 Objectives and Overview.- 1.5 Software Availability for Example Problems.- 2 Basic Theory of Simple Adaptive Control.- 2.1 Model Following.- 2.2 Output Model Following.- 2.3 Stability and Positivity Concepts.- 2.4 Adaptive Control Based on CGT.- 2.5 The Adaptive Algorithm with General Input Commands.- 2.6 Summary of Adaptive Algorithms.- Appendix 2A Proof of Theorem 2.1.- Appendix 2B Proof of Theorem 2.2.- Appendix 2C Poles, Zeros, and Relative Degree in Multivariable Systems.- 3 Extensions of the Basic Adaptive Algorithm.- 3.1 Parallel Feedforward and Stability Considerations.- 3.2 Feedforward Around Plant.- 3.3 Feedforward in Both Plant and Model.- 3.4 A Unified Approach to Supplementary Dynamics.- 3.5 Adaptive Control in the Presence of Nonlinearities.- 3.6 Summary.- Appendix 3A Proof of Positivity Lemmas.- Appendix 3B Proof of Theorem 3.1.- Appendix 3C Proof of Theorem 3.2.- Appendix 3D Proof of Theorem 3.3.- Appendix 3E Proof of Theorem 3.4.- Appendix 3F Outline of Proof of Theorem 3.5.- 4 Robust Design Procedures.- 4.1 Introduction.- 4.2 Robust Redesign of the Basic Adaptive Algorithm.- 4.3 Robustness Considerations with Feedforward in the Reference Model.- 4.4 Robust Redesign for Supplementary Dynamics.- 4.5 Bursting Phenomena and Their Elimination.- 4.6 Summary.- Appendix 4A Proof of Robust Stability, Theorem 4.1.- Appendix 4B Development of Lyapunov Function Derivative.- Appendix 4C Proof of Theorem 4.2.- 5 Adaptive Control of Time-Varying and Nonlinear Systems.- 5.1 Introduction.- 5.2 Passivity and Almost Passivity of Nonstationary Systems.- 5.3 Adaptive Control of ASP Plants.- 5.4 The "Almost Passivity" Lemmas.-5.5 Passivity and Almost Passivity of Nonlinear Systems.- 5.6 Simple Adaptive Control for a Class of Nonlinear Systems.- 5.7 Simple Adaptive Control of Rigid Robotic Manipulators.- 5.8 Summary.- Appendix 5A Proof of Stability for the Algorithm (5.27)-(5.32).- Appendix 5B Strictly Causal Almost Passive Systems.- Appendix 5C Proof of Lemma 5.1.- Appendix 5D Proof of Almost Passivity Lemma in Nonlinear Systems.- Appendix 5E Almost Passivity with Application to Manipulators.- Appendix 5F The Proof of Stability of the Adaptive Control Algorithm.- Appendix 5G Adaptive Control of Strictly Causal Almost Passive Systems.- 6 Design of Model Reference Adaptive Controllers.- 6.1 Algorithm Overview.- 6.2 Constraint Satisfaction.- 6.3 Weight Selection.- 6.4 Reference Model Selection.- 6.5 Digital Implementation.- 6.6 Time-Varying Commands.- Appendix 6A Proof of Theorem 6.1.- Appendix 6B Proof of Theorem 6.2.- Appendix 6C Proof of Lemma 6.1.- Appendix 6D Proof of Theorem 6.3.- 7 Case Studies.- 7.1 Direct Model Reference Adaptive Control of a PUMA Manipulator.- 7.2 Model Reference Adaptive Control of Large Structures.- 7.3 Adaptive Drug Delivery Control.- 7.4 Adaptive Control for a Relaxed Static Stability Aircraft.- 7.5 Liquid Level System Emulation.- References.
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