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An authoritative new exploration of the latest theoretical and applied advances in Linear Parameter-Varying systems In Linear Parameter-Varying Control: Theory and Application to Automotive Systems, distinguished researcher Dr. Olivier Sename delivers a comprehensive and up-to-date discussion of the theoretical aspects and real applications of Linear Parameter-Varying (LPV) control , with a strong focus on systems theory and in real automotive systems. The author covers the primary methods used to model, control, and analyze LPV systems, and illustrates how to model those systems using…mehr
An authoritative new exploration of the latest theoretical and applied advances in Linear Parameter-Varying systems
In Linear Parameter-Varying Control: Theory and Application to Automotive Systems, distinguished researcher Dr. Olivier Sename delivers a comprehensive and up-to-date discussion of the theoretical aspects and real applications of Linear Parameter-Varying (LPV) control, with a strong focus on systems theory and in real automotive systems. The author covers the primary methods used to model, control, and analyze LPV systems, and illustrates how to model those systems using examples.
This book covers developing adaptive LPV control using the provided recipes as guides and contextual aids as well as discovering effective methods to design LPV controllers that have already been validated through real applications.
Readers will also find:
A thorough introduction to vehicle dynamics control in automated vehicles, as well as suspension control
Comprehensive explorations of LPV systems modelling, including dynamical systems
Practical discussions of the properties of LPV systems, including controllability, observability, and stability
Complete treatments of LPV systems control, including state feedback control and dynamic output feedback LPV control
Perfect for researchers and students with an interest in vehicle dynamics, Linear Parameter-Varying Control will also benefit postgraduate and PhD students, control engineers, and academics teaching control theory and applications courses.
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Autorenporträt
Olivier Sename, PhD, is a full Professor at Grenoble INP. His main research focus is on Linear Parameter-Varying systems with automotive applications. He has authored or co-authored four books, around 100 international journal papers, more than 280 international conference papers and 6 patents.
Inhaltsangabe
About the Author xv Preface xvii Acronyms xxi About the Companion Website xxiii Introduction xxv Part I Some Theoretical Aspects on LPV Systems: From Modeling to Control 1 1 Some Modeling Approaches for LPV and qLPV Systems 3 1.1 Introduction 3 1.2 Dynamical Systems 4 1.3 An Introduction to LPV Models 5 1.4 Specific Classes of LPV Systems 10 1.5 From a Nonlinear Model to an LPV Representation 19 1.6 An Introduction to Identification of LPV Systems 23 1.7 The Nonuniqueness Issue: A Control-Oriented LPV Modeling Perspective 25 1.8 Illustrative Example 1: A Single Tank System 26 1.9 Illustrative Example 2: qLPV Modeling and Time-Varying Characteristics 30 1.10 Conclusion 34 Bibliography 34 2 Properties of LPV Systems 41 2.1 Introduction 41 2.2 Controllability 42 2.3 Observability 46 2.4 Comments on State-Space Realizations of LPV Systems 49 2.5 Stability 50 2.6 Performance Criteria: H , gH2, and Pole Placement 55 2.7 About Stabilizability and Detectability 62 2.8 The Case of Discrete-Time LPV Systems 63 2.9 Conclusion 68 Bibliography 68 3 Control of LPV Systems 75 3.1 Introduction 75 3.2 LPV State-Feedback Control 77 3.3 The LPV Dynamic Output Feedback Control 88 3.4 LPV Observer Design 104 3.5 About Control of Discrete-Time LPV Systems 109 3.6 Conclusion 111 Bibliography 111 Part II LPV Methods for Nonlinear Systems 121 4 Control and Observer Design for Nonlinear Systems Using Quasi-LPV Models: An Illustration Through Examples 123 4.1 Introduction 123 4.2 H LPV Control of a Nonlinear System 124 4.3 An H LPV Observer of a Three-Tank Nonlinear System 134 4.4 Conclusion 140 Bibliography 140 5 Observer Design for Semi-active Suspension Systems: qLPV Approaches 143 5.1 Introduction 143 5.2 Illustrative Case Study: The INOVE Testbench, a Semi-active Suspension System 145 5.3 Electro-Rheological Dampers: Modeling Approaches 147 5.4 qLPV Quarter Car Semi-active Suspension Models 152 5.5 Method 1: An H /gH2 Observer for Suspension State Estimation 158 5.6 Method 2: A H Filtering Approach for Damper Force Estimation 163 5.7 Method 3: A Nonlinear Parameter Varying Approach for State Estimation 168 5.8 Concluding Remarks 175 Bibliography 176 6 Lateral Control of Autonomous Vehicle 181 6.1 Introduction 181 6.2 Modeling 182 6.3 H LPV Control Design 187 6.4 Analysis of the Polytopic and Grid-Based Design Methods 191 6.5 Simulation Results 192 6.6 Conclusion 197 Bibliography 197 Part III LPV Adaptive-Like Control Methods 203 7 Methods and Tools for LPV Adaptive-Like Control 205 7.1 Introduction 205 7.2 The H Framework: A Generic Tool for "Adaptive-Like" Control 206 7.3 LPV Adaptive Control with Varying Closed-Loop Performances (Function of External Parameters) 208 7.4 LPV Adaptive Control Function of Varying Endogeneous Parameters 215 7.5 Concluding Remarks 223 Bibliography 223 8 LPV Road Adaptive Suspension Control 227 8.1 Introduction 227 8.2 The Semi-active Suspension Quarter-Car Model 230 8.3 Road Roughness Estimator 233 8.4 Synthesis of a Semi-active Suspension Control 237 8.5 Simulation Results 246 8.6 Conclusions 249 Bibliography 249 9 LPV Fault-Tolerant Control Strategies for Suspension Systems 257 9.1 Introduction 257 9.2 Related Works 259 9.3 Fault Diagnosis Problem Formulation for Semi-active ER Suspension Systems 261 9.4 Fault Estimation Using LPV PI Observers 265 9.5 FTC LPV Control of Semi-active Suspension Systems 276 9.6 Conclusion 284 Bibliography 284 10 Lateral LPV Adaptive-Like Control of Automated Vehicles Adapted to Driver Performance 293 10.1 Introduction 293 10.2 LPV Observer-Based Control Structure for ADAS Systems 294 10.3 Driver Fault Estimation Using a Discrete-Time LPV PI Observer 295 10.4 Robust H LPV ADAS Strategy 301 10.5 Simulation Results 308 10.6 Conclusion 313 Bibliography 313 Index 317
About the Author xv Preface xvii Acronyms xxi About the Companion Website xxiii Introduction xxv Part I Some Theoretical Aspects on LPV Systems: From Modeling to Control 1 1 Some Modeling Approaches for LPV and qLPV Systems 3 1.1 Introduction 3 1.2 Dynamical Systems 4 1.3 An Introduction to LPV Models 5 1.4 Specific Classes of LPV Systems 10 1.5 From a Nonlinear Model to an LPV Representation 19 1.6 An Introduction to Identification of LPV Systems 23 1.7 The Nonuniqueness Issue: A Control-Oriented LPV Modeling Perspective 25 1.8 Illustrative Example 1: A Single Tank System 26 1.9 Illustrative Example 2: qLPV Modeling and Time-Varying Characteristics 30 1.10 Conclusion 34 Bibliography 34 2 Properties of LPV Systems 41 2.1 Introduction 41 2.2 Controllability 42 2.3 Observability 46 2.4 Comments on State-Space Realizations of LPV Systems 49 2.5 Stability 50 2.6 Performance Criteria: H , gH2, and Pole Placement 55 2.7 About Stabilizability and Detectability 62 2.8 The Case of Discrete-Time LPV Systems 63 2.9 Conclusion 68 Bibliography 68 3 Control of LPV Systems 75 3.1 Introduction 75 3.2 LPV State-Feedback Control 77 3.3 The LPV Dynamic Output Feedback Control 88 3.4 LPV Observer Design 104 3.5 About Control of Discrete-Time LPV Systems 109 3.6 Conclusion 111 Bibliography 111 Part II LPV Methods for Nonlinear Systems 121 4 Control and Observer Design for Nonlinear Systems Using Quasi-LPV Models: An Illustration Through Examples 123 4.1 Introduction 123 4.2 H LPV Control of a Nonlinear System 124 4.3 An H LPV Observer of a Three-Tank Nonlinear System 134 4.4 Conclusion 140 Bibliography 140 5 Observer Design for Semi-active Suspension Systems: qLPV Approaches 143 5.1 Introduction 143 5.2 Illustrative Case Study: The INOVE Testbench, a Semi-active Suspension System 145 5.3 Electro-Rheological Dampers: Modeling Approaches 147 5.4 qLPV Quarter Car Semi-active Suspension Models 152 5.5 Method 1: An H /gH2 Observer for Suspension State Estimation 158 5.6 Method 2: A H Filtering Approach for Damper Force Estimation 163 5.7 Method 3: A Nonlinear Parameter Varying Approach for State Estimation 168 5.8 Concluding Remarks 175 Bibliography 176 6 Lateral Control of Autonomous Vehicle 181 6.1 Introduction 181 6.2 Modeling 182 6.3 H LPV Control Design 187 6.4 Analysis of the Polytopic and Grid-Based Design Methods 191 6.5 Simulation Results 192 6.6 Conclusion 197 Bibliography 197 Part III LPV Adaptive-Like Control Methods 203 7 Methods and Tools for LPV Adaptive-Like Control 205 7.1 Introduction 205 7.2 The H Framework: A Generic Tool for "Adaptive-Like" Control 206 7.3 LPV Adaptive Control with Varying Closed-Loop Performances (Function of External Parameters) 208 7.4 LPV Adaptive Control Function of Varying Endogeneous Parameters 215 7.5 Concluding Remarks 223 Bibliography 223 8 LPV Road Adaptive Suspension Control 227 8.1 Introduction 227 8.2 The Semi-active Suspension Quarter-Car Model 230 8.3 Road Roughness Estimator 233 8.4 Synthesis of a Semi-active Suspension Control 237 8.5 Simulation Results 246 8.6 Conclusions 249 Bibliography 249 9 LPV Fault-Tolerant Control Strategies for Suspension Systems 257 9.1 Introduction 257 9.2 Related Works 259 9.3 Fault Diagnosis Problem Formulation for Semi-active ER Suspension Systems 261 9.4 Fault Estimation Using LPV PI Observers 265 9.5 FTC LPV Control of Semi-active Suspension Systems 276 9.6 Conclusion 284 Bibliography 284 10 Lateral LPV Adaptive-Like Control of Automated Vehicles Adapted to Driver Performance 293 10.1 Introduction 293 10.2 LPV Observer-Based Control Structure for ADAS Systems 294 10.3 Driver Fault Estimation Using a Discrete-Time LPV PI Observer 295 10.4 Robust H LPV ADAS Strategy 301 10.5 Simulation Results 308 10.6 Conclusion 313 Bibliography 313 Index 317
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