| Description |
1 online resource (xxiv, 352 pages) : illustrations |
| Contents |
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 |
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-- 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 |
| Summary |
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 derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. The book provides results that are rigorously proved and accompanied by examples with numerical simulations or experiments. -- Edited summary from book |
| Bibliography |
Includes bibliographical references (pages 337-352) |
| Notes |
Print version record |
| Subject |
Adaptive control systems.
|
|
Adaptive control systems
|
| Form |
Electronic book
|
| Author |
Jin, Shangtai
|
| LC no. |
2013028518 |
| ISBN |
1466594187 |
|
9781466594180 |
|
9781466594197 |
|
1466594195 |
|
