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Model free adaptive control : theory and applications /

This book summarizes theory and applications of model-free adaptive control (MFAC), which is a pure data-driven model-free control method, and whose controller design and stability analysis merely depend on the measured input and output data of the controlled plants. Topics include: pseudo partial d...

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Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autor principal:	Hou, Zhongsheng
Otros Autores:	Jin, Shangtai
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Boca Raton, FL : CRC Press, ©2014.
Temas:	Adaptive control systems. Systèmes adaptatifs.
Acceso en línea:	Texto completo (Requiere registro previo con correo institucional)

Tabla de Contenidos:

1 Introduction 1
1.1 Model-Based Control 1
1.1.1 Modeling and Identification 1
1.1.2 Model-Based Controller Design 3
1.2 Data-Driven Control 5
1.2.1 Definition and Motivation of Data-Driven Control 6
1.2.2 Object of Data-Driven Control Methods 7
1.2.3 Necessity of Data-Driven Control Theory and Methods 8
1.2.4 Brief Survey on Data-Driven Control Methods 10
1.2.4.1 DDC Classification According to Data Usage 10
1.2.4.2 DDC Classification According to Controller Structure Design 14
1.2.5 Summary of Data-Driven Control Methods 15
1.3 Preview of the Book 17
2 Recursive Parameter Estimation for Discrete-Time Systems 19
2.1 Introduction 19
2.2 Parameter Estimation Algorithm for Linearly Parameterized Systems 20
2.2.1 Projection Algorithm 21
2.2.2 Least-Squares Algorithm 22
2.2.2.1 Least-Squares Algorithm for Time-Invariant Parameter Estimation 22
2.2.2.2 Modified Least-Squares Algorithm for Time-Varying Parameter Estimation 24
2.3 Parameter Estimation Algorithm for Nonlinearly Parameterized Systems 27
2.3.1 Projection Algorithm and Its Modified Form for Nonlinearly Parameterized Systems 27
2.3.1.1 Existing Projection Algorithm 27
2.3.1.2 Modified Projection Algorithm 28
2.3.2 Least-Squares Algorithm and Its Modified Form for Nonlinearly Parameterized Systems 32
2.3.2.1 Existing Least-Squares Algorithm 32
2.3.2.2 Modified Least-Squares Algorithm 34
2.4 Conclusions 44
3 Dynamic Linearization Approach of Discrete-Time Nonlinear Systems 45
3.1 Introduction 45
3.2 SISO Discrete-Time Nonlinear Systems 47
3.2.1 Compact Form Dynamic Linearization 47
3.2.2 Partial Form Dynamic Linearization 53
3.2.3 Full Form Dynamic Linearization 59
3.3 MIMO Discrete-Time Nonlinear Systems 64
3.3.1 Compact Form Dynamic Linearization 64
3.3.2 Partial Form Dynamic Linearization 66
3.3.3 Full Form Dynamic Linearization 69
3.4 Conclusions 71
4 Model-Free Adaptive Control of SISO Discrete-Time Nonlinear Systems 75
4.1 Introduction 75
4.2 CFDL Data Model Based MFAC 77
4.2.1 Control System Design 77
4.2.1.1 Controller Algorithm 77
4.2.1.2 PPD Estimation Algorithm 78
4.2.1.3 System Control Scheme 79
4.2.2 Stability Analysis 80
4.2.3 Simulation Results 87
4.3 PFDL Data Model Based MFAC 93
4.3.1 Control System Design 93
4.3.1.1 Controller Algorithm 94
4.3.1.2 PG Estimation Algorithm 94
4.3.1.3 System Control Scheme 95
4.3.2 Stability Analysis 96
4.3.3 Simulation Results 104
4.4 FFDL Data Model Based MFAC 108
4.4.1 Control System Design 108
4.4.1.1 Controller Algorithm 110
4.4.1.2 PG Estimation Algorithm 111
4.4.1.3 System Control Scheme 111
4.4.2 Simulation Results 113
4.5 Conclusions H8
5 Model-Free Adaptive Control of MIMO Discrete-Time Nonlinear Systems 119
5.1 Introduction 119
5.2 CFDL Data Model Based MFAC 120
5.2.1 Control System Design 120
5.2.1.1 Controller Algorithm 121
5.2.1.2 PJM Estimation Algorithm 122
5.2.1.3 System Control Scheme 123
5.2.2 Stability Analysis 124
5.2.3 Simulation Results 132
5.3 PFDL Data Model Based MFAC 134
5.3.1 Control System Design 134
5.3.1.1 Controller Algorithm 136
5.3.1.2 PPJM Estimation Algorithm 137
5.3.1.3 System Control Scheme 138
5.3.2 Stability Analysis 139
5.3.3 Simulation Results 145
5.4 FFDL Data Model Based MFAC 149
5.4.1 Control System Design 149
5.4.1.1 Controller Algorithm 150
5.4.1.2 PPJM Estimation Algorithm 151
5.4.1.3 System Control Scheme 152
5.4.2 Simulation Results 153
5.5 Conclusions 156
6 Model-Free Adaptive Predictive Control 157
6.1 Introduction 157
6.2 CFDL Data Model Based MFAPC 158
6.2.1 Control System Design 158
6.2.1.1 Controller Algorithm 160
6.2.1.2 PPD Estimation Algorithm and Prediction Algorithm 161
6.2.1.3 Control Scheme 162
6.2.2 Stability Analysis 164
6.2.3 Simulation Results 167
6.3 PFDL Data Model Based MFAPC 171
6.3.1 Control System Design 171
6.3.1.1 Controller Algorithm 174
6.3.1.2 PG Estimation Algorithm and Prediction Algorithm 174
6.3.1.3 Control Scheme 176
6.3.2 Simulation Results 177
6.4 FFDL Data Model Based MFAPC 182
6.4.1 Control System Design 182
6.4.1.1 Controller Algorithm 184
6.4.1.2 PG Estimation Algorithm 185
6.4.1.3 Control Scheme 186
6.4.2 Simulation Results 188
6.5 Conclusions 190
7 Model-Free Adaptive Iterative Learning Control 193
7.1 Introduction 193
7.2 CFDL Data Model Based MFAILC 195
7.2.1 CFDL Data Model in the Iteration Domain 195
7.2.2 Control System Design 198
7.2.2.1 Controller Algorithm 198
7.2.2.2 PPD Iterative Updating Algorithm 199
7.2.2.3 CFDL-MFAILC Scheme 199
7.2.3 Convergence Analysis 200
7.2.4 Simulation Results 204
7.3 Conclusions 205
8 Model-Free Adaptive Control for Complex Connected Systems and Modularized Controller Design 207
8.1 Introduction 207
8.2 MFAC for Complex Connected Systems 208
8.2.1 Series Connection 209
8.2.2 Parallel Connection 212
8.2.3 Feedback Connection 214
8.2.4 Complex Interconnection 217
8.2.5 Simulation Results 219
8.2.5.1 Series, Parallel, and Feedback Connection 219
8.2.5.2 Complex Interconnection 220
8.3 Modularized Controller Design 223
8.3.1 Estimation-Type Control System Design 223
8.3.2 Embedded-Type Control System Design 229
8.3.2.1 Embedded-Type Control System Design for Nonrepetitive Systems 229
8.3.2.2 Modularized Controller Design Scheme for Repetitive Systems 232
8.3.3 Simulations 235
8.4 Conclusions 238
9 Robustness of Model-Free Adaptive Control 241
9.1 Introduction 241
9.2 MFAC in the Presence of Output Measurement Noise 242
9.2.1 Robust Stability Analysis 242
9.2.2 Simulations 247
9.3 MFAC in the Presence of Data Dropouts 247
9.3.1 Robust Stability Analysis 249
9.3.2 MFAC Scheme with Data-Dropped Compensation 252
9.3.3 Simulations 258
9.4 Conclusions 259
10 Symmetric Similarity for Control System Design 261
10.1 Introduction 261
10.2 Symmetric Similarity for Adaptive Control Design 263
10.2.1 Concepts and Design Principle of Symmetric Similarity 264
10.2.2 Adaptive Control with Symmetric Similarity Structure 266
10.2.2.1 Adaptive Control with Symmetric Similarity Structure for Linear Systems 266
10.2.2.2 Adaptive Control with Symmetric Similarity Structure for Nonlinear Systems 270
10.2.3 MFAC with Symmetric Similarity Structure 272
10.2.4 Simulations 273
10.2.4.1 Adaptive Control with Symmetric Similarity Structure 276
10.2.4.2 MFAC with Symmetric Similarity Structure 278
10.3 Similarity between MFAC and MFAILC 280
10.4 Similarity between Adaptive Control and Iterative Learning Control 283
10.4.1 Adaptive Control for Discrete-Time Nonlinear Systems 287
10.4.1.1 Problem Formulation 287
10.4.1.2 Adaptive Control Design 287
10.4.1.3 Stability and Convergence Analysis 288
10.4.2 Adaptive ILC for Discrete-Time Nonlinear Systems 293
10.4.2.1 Problem Formulation 293
10.4.2.2 Adaptive Iterative Learning Control Design 293
10.4.2.3 Stability and Convergence Analysis 294
10.4.3 Comparison between Adaptive Control and Adaptive ILC 301
10.5 Conclusions 304
11 Applications 305
11.1 Introduction 305
11.2 Three-Tank Water System 306
11.2.1 Experimental Setup 306
11.2.2 Three Data-Driven Control Schemes 308
-- 11.2.2.1 MFAC Scheme 308
11.2.2.2 VRFT Method 308
11.2.2.3 IFT Method 309
11.2.3 Experimental Investigation 309
11.2.3.1 Experiment I 309
11.2.3.2 Experiment II 314
11.3 Permanent Magnet Linear Motor 314
11.3.1 Permanent Magnet Linear Motor System 316
11.3.1.1 Experimental Setup 316
11.3.1.2 MFAC Scheme 317
11.3.1.3 Experiments 319
11.3.2 Dual-Axis Linear Motor Gantry System 325
11.3.2.1 Experimental Setup 325
11.3.2.2 MFAC Scheme for the Dual-Axis Linear Motor Gantry System 326
11.3.2.3 Experiments 326
11.4 Freeway Traffic System 329
11.4.1 Macroscopic Traffic Model 331
11.4.2 Control Scheme 333
11.4.3 Simulations 334
11.5 Welding Process 339
11.5.1 Experimental Setup 339
11.5.2 Control Scheme 340
11.5.3 Simulations 341
11.5.4 Experimental Investigation 341
11.6 MW Grade Wind Turbine 343
11.6.1 Wind Turbine Blade Static Loading Control System 345
11.6.2 Control Scheme 346
11.6.3 Static Loading Experiment 347
11.7 Conclusions 348
12 Conclusions and Perspectives 351
12.1 Conclusions 351
12.2 Perspectives 353.

Model free adaptive control : theory and applications /

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