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Engineering - Robotics | Direct Adaptive Control Algorithms: - Theory and Applications

Direct Adaptive Control Algorithms:

Theory and Applications

Kaufman, Howard, Barkana, Itzhak, Sobel, Kenneth

Softcover reprint of the original 1st ed. 1994, XXIII, 370 pp. 154 figs.

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Suitable either as a reference or as a text for a graduate course in adaptive control systems, this book is a self-contained compendium of easily implementable adaptive control algorithms that have been developed and applied by the authors for over 10 years. These algorithms do not require explicit process parameter identification and have been successfully applied to a wide variety of engineering problems including flexible structure control, blood pressure control and robotics. In general, these algorithms are suitable for a wide class of multiple input-output control systems containing significant uncertainty as well as disturbances.

Content Level » Research

Keywords » adaptive control - algorithms - control - control algorithm - control system - robot - robotics - uncertainty

Related subjects » Robotics

Table of contents 

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.- 1.4.1 Objectives.- 1.4.2 Relation with Other Texts.- 1.4.3 Overview of Text.- 2 Basic Theory of Simple Adaptive Control.- 2.1 Model Following.- 2.2 Output Model Following.- 2.2.1 Command Generator Tracker Description.- 2.2.2 Modifications for the Tracking of A Larger Class of Input Commands.- 2.2.3 The General Tracking Problem.- 2.3 Stability and Positivity Concepts.- 2.3.1 Introduction: Stability with Fixed Controllers Versus Nonlinear Adaptive Controllers.- 2.3.2 Basic Stability Concepts.- 2.3.3 Positive Real Analysis.- 2.4 Adaptive Control Based on CGT.- 2.4.1 Controller Structure.- 2.4.2 Stability Analysis.- 2.4.3 System Constraints.- 2.4.4 An Illustrative Example.- 2.5 The Adaptive Algorithm with General Input Commands 63 2.5.1 Controller Structure.- 2.5.2 Stability Analysis.- 2.5.3 An Illustrative Example.- 2.6 Summary of Adaptive Algorithms.- 2A Proof of Theorem 2.1.- 2B Proof of Theorem 2.2.- 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.- 3.2.1 Adaptive Control with Basic Feedforward Augmentation.- 3.2.2 Summary of MRAC Using Plant Feedforward.- 3.2.3 Illustrative Examples.- 3.3 Feedforward in Both Plant and Model.- 3.3.1 Modifications to Insure Asymptotic Model Following.- 3.3.2 Stability Proof.- 3.3.3 Summary of Constraints and Design Rules Ill.- 3.3.4 Illustrative Examples.- 3.3.5 Conclusions and Recommendations.- 3.4 A Unified Approach to Supplementary Dynamics.- 3.4.1 Theory.- 3.4.2 Summary of Constraints and Design Rules.- 3.4.3 Illustrative Examples.- 3.5 Adaptive Control in the Presence of Nonlinearities.- 3.5.1 Theory.- 3.5.2 Adaptation for Nonlinearity of Known Form.- 3.6 Summary.- 3A Proof of Positivity Lemmas.- 3B Proof of Theorem 3.1.- 3C Proof of Theorem 3.2.- 3D Proof of Theorem 3.3.- 3E Proof of Theorem 3.4.- 4 Robust Design Procedures.- 4.1 Introduction.- 4.2 Robust Redesign of the Basic Adaptive Algorithm.- 4.2.1 Algorithm Description.- 4.2.2 Illustrative Examples.- 4.3 Robustness Considerations with Feedforward in the Reference Model.- 4.3.1 Algorithm Description.- 4.3.2 Illustrative Examples.- 4.4 Robust Redesign for Supplementary Dynamics.- 4.4.1 Algorithm Description.- 4.4.2 Error System Equations.- 4.4.3 Stability Analysis.- 4.4.4 Illustrative Examples.- 4.5 Bursting Phenomena and Their Elimination.- 4.6 Summary.- 4A Proof of Robust Stability, Theorem 1.- 4B Development of Lyapunov Function Derivative.- 4C Proof of Theorem 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 Adaptive Control of Nonlinear Systems.- 5A Proof of Stability for the Algorithm (5.27)–(5.32).- 5B Strictly Causal Almost Passive Systems.- 5C Proof of Lemma 1.- 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.- 6.6.1 Command Generated as Output of Linear System.- 6.6.2 Command Variations Slow Compared with Reference Model.- 7 Case Studies.- 7.1 Direct Model Reference Adaptive Control of a PUMA Manipulator.- 7.1.1 Introduction.- 7.1.2 Puma Model Development.- 7.1.3 Implementation Issues.- 7.1.4 Simulation Results.- 7.1.5 Experimental Results.- 7.1.6 Conclusions and Recommendations.- 7.2 Model Reference Adaptive Control of Large Structures.- 7.2.1 Introduction.- 7.2.2 Large Flexible Structures (LFS) Dynamics.- 7.2.3 The ASPR Condition for Flexible Structures.- 7.2.4 Adaptive Control Algorithm.- 7.2.5 Experimental Set-Up.- 7.2.6 Experiment Results and Discussion.- 7.3 Adaptive Drug Delivery Control.- 7.3.1 Introduction.- 7.3.2 Problem Statement.- 7.3.3 Controller Design.- 7.3.4 Operation of the Complete Hierarchical Controller.- 7.3.5 Experimental Results.- 7.3.6 Conclusions.- 7.4 Adaptive Control for a Relaxed Static Stability Aircraft.- 7.4.1 Introduction.- 7.4.2 Model Development.- 7.4.3 Control Law Development.- 7.4.4 Conclusions.- References.

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