Titre :	Adaptive control : algorithms, analysis and applications
Type de document :	texte imprimé
Auteurs :	Ioan D. Landau, Auteur ; Rogelio Lozano, Auteur ; Mohammed M'Saad, Auteur
Mention d'édition :	2 ème ed.
Editeur :	New York, Dordrecht, Heidelberg : Springer
Année de publication :	2011
Importance :	587 p.
Présentation :	couv. ill. en coul., ill.
Format :	24,5 cm.
ISBN/ISSN/EAN :	978-0-85729-663-4
Langues :	Anglais (eng)
Catégories :	AUTOMATISME
Index. décimale :	25-07 Théorie de la commande: commandes des processus
Résumé :	Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant.
Note de contenu :	Contents 1: Introduction to Adaptive Control 1.1 Adaptive Control-Why? 1.2 Adaptive Control Versus Conventional Feedback Control 1.3 Basic Adaptive Control Schemes 1.4 Examples of Applications 1.5 A Brief Historical Note 1.6 Further Reading 1.7 Concluding Remarks 2: Discrete-Time System Models for Control 2.1 Deterministic Environment 2.2 Stochastic Environment 2.3 Concluding Remarks 2.4 Problems 3: Parameter Adaptation Algorithms-Deterministic Environment 3.1 The Problem 3.2 Parameter Adaptation Algorithms (PAA)-Examples 3.3 Stability of Parameter Adaptation Algorithms 3.4 Parametric Convergence 3.5 Concluding Remarks 3.6 Problems 4: Parameter Adaptation Algorithms-Stochastic Environment 4.1 Effect of Stochastic Disturbances 4.2 The Averaging Method for the Analysis of Adaptation Algorithms in a Stochastic Environment 4.3 The Martingale Approach for the Analysis of PAA in a Stochastic Environment 4.4 The Frequency Domain Approach 4.5 Concluding Remarks 4.6 Problem 5: Recursive Plant Model Identification in Open Loop 5.1 Recursive Identification in the Context of System Identification 5.2 Structure of Recursive Parameter Estimation Algorithms 5.3 Recursive Identification Methods Based on the Whitening of the the prediction error type I 5.4 Validation of the Models Identified with Type I Methods 5.5 Identification Methods Based on the Decorrelation of the Observation vector and the prediction error type II 5.6 Validation of the Models Identified with Type II Methods 5.7 Selection of the Pseudo Random Binary Sequence 5.8 Model Order Selection 5.9 An Example: Identification of a Flexible Transmission 5.10 Concluding Remarks 5.11 Problems 6: Adaptive Prediction 6.1 The Problem 6.2 Adaptive Prediction-Deterministic Case 6.3 Adaptive Prediction-Stochastic Case 6.4 Concluding Remarks 6.5 Problems 7: Digital Control Strategies 7.1 Introduction 7.2 Canonical Form for Digital Controllers 7.3 Pole Placement 7.4 Tracking and Regulation with Independent Objectives 7.5 Tracking and Regulation with Weighted Input 7.6 Minimum Variance Tracking and Regulation 7.7 Generalized Predictive Control 7.8 Linear Quadratic Control 7.9 Concluding Remarks 7.10 Problems 8: Robust Digital Control Design 8.1 The Robustness Problem 8.2 The Sensitivity Functions 8.3 Robust Stability 8.4 Definition of "Templates" for the Sensitivity Functions 8.5 Properties of the Sensitivity Functions 8.6 Shaping the Sensitivity Functions 8.7 Other Design Methods 8.8 A Design Example: Robust Digital Control of a Flexible Transmission 8.9 Concluding Remarks 8.10 Problems 9: Recursive Plant Model Identification in Closed Loop 9.1 The Problem 9.2 Closed-Loop Output Error Algorithms (CLOE) 9.3 Filtered Open-Loop Recursive Identification Algorithms (FOL) 9.4 Frequency Distribution of the Asymptotic Bias in Closed-Loop Identification 9.5 Validation of Models Identified in Closed-Loop 9.6 Iterative Identification in Closed-Loop and Controller Redesign 9.7 Comparative Evaluation of the Various Algorithms 9.8 Iterative Identification in Closed Loop and Controller Redesign Applied to the Flexible Transmis 9.9 Concluding Remarks 9.10 Problems 10: Robust Parameter Estimation 10.1 The Problem 10.2 Input/Output Data Filtering 10.3 Effect of Disturbances 10.4 PAA with Dead Zone 10.5 PAA with Projection 10.6 Data Normalization 10.7 A Robust Parameter Estimation Scheme 10.8 Concluding Remarks 10.9 Problems 11: Direct Adaptive Control 11.1 Introduction 11.2 Adaptive Tracking and Regulation with Independent Objectives 11.3 Adaptive Tracking and Regulation with Weighted Input 11.4 Adaptive Minimum Variance Tracking and Regulation 11.5 Robust Direct Adaptive Control 11.6 An Example 11.7 Concluding Remarks 11.8 Problems 12: Indirect Adaptive Control 12.1 Introduction 12.2 Adaptive Pole Placement 12.3 Robust Indirect Adaptive Control 12.4 Adaptive Generalized Predictive Control 12.5 Adaptive Linear Quadratic Control 12.6 Adaptive Tracking and Robust Regulation 12.7 Indirect Adaptive Control Applied to the Flexible Transmission 12.8 Concluding Remarks 12.9 Problems 13: Multimodel Adaptive Control with Switching 13.1 Introduction 13.2 Princip13.3les of Multimodel Adaptive Control with Switching 13.3 Stability Issues 13.4 Application to the Flexible Transmission System 13.5 Concluding Remarks 13.6 Problems 14: Adaptive Regulation-Rejection of Unknown Disturbances 14.1 Introduction 14.2 Plant Representation and Controller Design 14.3 Robustness Considerations 14.4 Direct Adaptive Regulation 14.5 Stability Analysis 14.6 Indirect Adaptive Regulation 14.7 Adaptive Rejection of Multiple Narrow Band Disturbances on an Active Vibration Control System 14.8 Concluding Remarks 14.9 Problems 15: Adaptive Feedforward Compensation of Disturbances 15.1 Introduction 15.2 Basic Equations and Notations 15.3 Development of the Algorithms 15.4 Analysis of the Algorithms 15.5 Adaptive Attenuation of Broad Band Disturbances on an Active Vibration Control System 15.6 Concluding Remarks 15.7 Problems 16: Practical Aspects 16.1 Introduction 16.2 The Digital Control System 16.2.1 Selection of the Sampling Frequency 16.2.2 Anti-Aliasing Filters 16.2.3 Digital Controller 16.2.4 Effects of the Digital to Analog Converter 16.2.5 Handling Actuator Saturations (Anti-Windup) 16.2.6 Manual to Automatic Bumpless Transfer 16.2.7 Effect of the Computational Delay 16.2.8 Choice of the Desired Performance 16.3 The Parameter Adaptation Algorithm 16.3.1 Scheduling Variable alpha1(t) 16.3.2 Implementation of the Adaptation Gain Updating-The U-D Factorization 16.4 Adaptive Control Algorithms 16.4.1 Control Strategies 16.4.2 Adaptive Control Algorithms 16.5 Initialization of Adaptive Control Schemes 16.6 Monitoring of Adaptive Control Systems 16.7 Concluding Remarks Appendix A: Stochastic Processes Appendix B: Stability Appendix C: Passive (Hyperstable) Systems C.1 Passive (Hyperstable) Systems C.2 Passivity-Some Definitions C.3 Discrete Linear Time-Invariant Passive Systems C.4 Discrete Linear Time-Varying Passive Systems C.5 Stability of Feedback Interconnected Systems C.6 Hyperstability and Small Gain Appendix D: Martingales References Index

Adaptive control : algorithms, analysis and applications [texte imprimé] / Ioan D. Landau, Auteur ; Rogelio Lozano, Auteur ; Mohammed M'Saad, Auteur  . -  2 ème ed. . - New York, Dordrecht, Heidelberg : Springer, 2011 . - 587 p. : couv. ill. en coul., ill. ; 24,5 cm.
ISBN : 978-0-85729-663-4
Langues : Anglais (eng)

Catégories :	AUTOMATISME
Index. décimale :	25-07 Théorie de la commande: commandes des processus
Résumé :	Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant.
Note de contenu :	Contents 1: Introduction to Adaptive Control 1.1 Adaptive Control-Why? 1.2 Adaptive Control Versus Conventional Feedback Control 1.3 Basic Adaptive Control Schemes 1.4 Examples of Applications 1.5 A Brief Historical Note 1.6 Further Reading 1.7 Concluding Remarks 2: Discrete-Time System Models for Control 2.1 Deterministic Environment 2.2 Stochastic Environment 2.3 Concluding Remarks 2.4 Problems 3: Parameter Adaptation Algorithms-Deterministic Environment 3.1 The Problem 3.2 Parameter Adaptation Algorithms (PAA)-Examples 3.3 Stability of Parameter Adaptation Algorithms 3.4 Parametric Convergence 3.5 Concluding Remarks 3.6 Problems 4: Parameter Adaptation Algorithms-Stochastic Environment 4.1 Effect of Stochastic Disturbances 4.2 The Averaging Method for the Analysis of Adaptation Algorithms in a Stochastic Environment 4.3 The Martingale Approach for the Analysis of PAA in a Stochastic Environment 4.4 The Frequency Domain Approach 4.5 Concluding Remarks 4.6 Problem 5: Recursive Plant Model Identification in Open Loop 5.1 Recursive Identification in the Context of System Identification 5.2 Structure of Recursive Parameter Estimation Algorithms 5.3 Recursive Identification Methods Based on the Whitening of the the prediction error type I 5.4 Validation of the Models Identified with Type I Methods 5.5 Identification Methods Based on the Decorrelation of the Observation vector and the prediction error type II 5.6 Validation of the Models Identified with Type II Methods 5.7 Selection of the Pseudo Random Binary Sequence 5.8 Model Order Selection 5.9 An Example: Identification of a Flexible Transmission 5.10 Concluding Remarks 5.11 Problems 6: Adaptive Prediction 6.1 The Problem 6.2 Adaptive Prediction-Deterministic Case 6.3 Adaptive Prediction-Stochastic Case 6.4 Concluding Remarks 6.5 Problems 7: Digital Control Strategies 7.1 Introduction 7.2 Canonical Form for Digital Controllers 7.3 Pole Placement 7.4 Tracking and Regulation with Independent Objectives 7.5 Tracking and Regulation with Weighted Input 7.6 Minimum Variance Tracking and Regulation 7.7 Generalized Predictive Control 7.8 Linear Quadratic Control 7.9 Concluding Remarks 7.10 Problems 8: Robust Digital Control Design 8.1 The Robustness Problem 8.2 The Sensitivity Functions 8.3 Robust Stability 8.4 Definition of "Templates" for the Sensitivity Functions 8.5 Properties of the Sensitivity Functions 8.6 Shaping the Sensitivity Functions 8.7 Other Design Methods 8.8 A Design Example: Robust Digital Control of a Flexible Transmission 8.9 Concluding Remarks 8.10 Problems 9: Recursive Plant Model Identification in Closed Loop 9.1 The Problem 9.2 Closed-Loop Output Error Algorithms (CLOE) 9.3 Filtered Open-Loop Recursive Identification Algorithms (FOL) 9.4 Frequency Distribution of the Asymptotic Bias in Closed-Loop Identification 9.5 Validation of Models Identified in Closed-Loop 9.6 Iterative Identification in Closed-Loop and Controller Redesign 9.7 Comparative Evaluation of the Various Algorithms 9.8 Iterative Identification in Closed Loop and Controller Redesign Applied to the Flexible Transmis 9.9 Concluding Remarks 9.10 Problems 10: Robust Parameter Estimation 10.1 The Problem 10.2 Input/Output Data Filtering 10.3 Effect of Disturbances 10.4 PAA with Dead Zone 10.5 PAA with Projection 10.6 Data Normalization 10.7 A Robust Parameter Estimation Scheme 10.8 Concluding Remarks 10.9 Problems 11: Direct Adaptive Control 11.1 Introduction 11.2 Adaptive Tracking and Regulation with Independent Objectives 11.3 Adaptive Tracking and Regulation with Weighted Input 11.4 Adaptive Minimum Variance Tracking and Regulation 11.5 Robust Direct Adaptive Control 11.6 An Example 11.7 Concluding Remarks 11.8 Problems 12: Indirect Adaptive Control 12.1 Introduction 12.2 Adaptive Pole Placement 12.3 Robust Indirect Adaptive Control 12.4 Adaptive Generalized Predictive Control 12.5 Adaptive Linear Quadratic Control 12.6 Adaptive Tracking and Robust Regulation 12.7 Indirect Adaptive Control Applied to the Flexible Transmission 12.8 Concluding Remarks 12.9 Problems 13: Multimodel Adaptive Control with Switching 13.1 Introduction 13.2 Princip13.3les of Multimodel Adaptive Control with Switching 13.3 Stability Issues 13.4 Application to the Flexible Transmission System 13.5 Concluding Remarks 13.6 Problems 14: Adaptive Regulation-Rejection of Unknown Disturbances 14.1 Introduction 14.2 Plant Representation and Controller Design 14.3 Robustness Considerations 14.4 Direct Adaptive Regulation 14.5 Stability Analysis 14.6 Indirect Adaptive Regulation 14.7 Adaptive Rejection of Multiple Narrow Band Disturbances on an Active Vibration Control System 14.8 Concluding Remarks 14.9 Problems 15: Adaptive Feedforward Compensation of Disturbances 15.1 Introduction 15.2 Basic Equations and Notations 15.3 Development of the Algorithms 15.4 Analysis of the Algorithms 15.5 Adaptive Attenuation of Broad Band Disturbances on an Active Vibration Control System 15.6 Concluding Remarks 15.7 Problems 16: Practical Aspects 16.1 Introduction 16.2 The Digital Control System 16.2.1 Selection of the Sampling Frequency 16.2.2 Anti-Aliasing Filters 16.2.3 Digital Controller 16.2.4 Effects of the Digital to Analog Converter 16.2.5 Handling Actuator Saturations (Anti-Windup) 16.2.6 Manual to Automatic Bumpless Transfer 16.2.7 Effect of the Computational Delay 16.2.8 Choice of the Desired Performance 16.3 The Parameter Adaptation Algorithm 16.3.1 Scheduling Variable alpha1(t) 16.3.2 Implementation of the Adaptation Gain Updating-The U-D Factorization 16.4 Adaptive Control Algorithms 16.4.1 Control Strategies 16.4.2 Adaptive Control Algorithms 16.5 Initialization of Adaptive Control Schemes 16.6 Monitoring of Adaptive Control Systems 16.7 Concluding Remarks Appendix A: Stochastic Processes Appendix B: Stability Appendix C: Passive (Hyperstable) Systems C.1 Passive (Hyperstable) Systems C.2 Passivity-Some Definitions C.3 Discrete Linear Time-Invariant Passive Systems C.4 Discrete Linear Time-Varying Passive Systems C.5 Stability of Feedback Interconnected Systems C.6 Hyperstability and Small Gain Appendix D: Martingales References Index