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Adaptive and Robust Active Vibration Control - Methodology and Tests
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Adaptive and Robust Active Vibration Control - Methodology and Tests
von: Ioan D. Landau, Tudor-Bogdan Airimițoaie, Abraham Castellanos-Silva, Aurelian Constantinescu
Springer-Verlag, 2016
ISBN: 9783319414508
405 Seiten, Download: 20257 KB
 
Format: PDF
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Typ: B (paralleler Zugriff)

 

 
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Inhaltsverzeichnis

  Series Editors’ Foreword 7  
  Preface 9  
     Website 10  
     Expected Audience 11  
     About the Content 11  
     Pathways Through the Book 12  
     Acknowledgements 14  
     References[1] Constantinescu, A.: Commande robuste et adaptative d’une suspension active. Thèse de doctorat, Institut National Polytechnique de Grenoble (2001)[2] Alma, M.: Rejet adaptatif de perturbations en contrôle actif de vibrations. Ph.D. thesis, Université de Grenoble (2011)[3] Airimitoaie, T.B.: Robust design and tuning of active vibration control systems. Ph.D. thesis, University of Grenoble, France, and University “Politehnica” of Bucharest, Romania (2012)[4] Castellanos-Silva, A.: Compensation adaptative par feedback pour le contrôle actif de vibrations en présence d’incertitudes sur les paramétres du procédé. Ph.D. thesis, Université de Grenoble (2014)[5] Landau, I.D., Silva, A.C., Airimitoaie, T.B., Buche, G., Noé, M.: Benchmark on adaptive regulation—rejection of unknown/time-varying multiple narrow band disturbances. European Journal of Control 19(4), 237—252 (2013). http://dx.doi.org/10.1016/j.ejcon.2013.05.007#1 14  
  Contents 15  
  Acronyms 23  
  Part I Introduction to Adaptive and Robust Active Vibration Control 25  
  1 Introduction to Adaptive and Robust Active Vibration Control 26  
     1.1 Active Vibration Control: Why and How 26  
     1.2 A Conceptual Feedback Framework 32  
     1.3 Active Damping 34  
     1.4 The Robust Regulation Paradigm 34  
     1.5 The Adaptive Regulation Paradigm 35  
     1.6 Concluding Remarks 37  
     1.7 Notes and Reference 38  
     References 38  
  2 The Test Benches 41  
     2.1 An Active Hydraulic Suspension System Using Feedback Compensation 41  
     2.2 An Active Vibration Control System Using Feedback Compensation Through an Inertial Actuator 44  
     2.3 An Active Distributed Flexible Mechanical Structure ƒ 46  
     2.4 Concluding Remarks 49  
     2.5 Notes and References 50  
     References 50  
  Part II Techniques for Active Vibration Control 51  
  3 Active Vibration Control Systems---Model Representation 52  
     3.1 System Description 52  
        3.1.1 Continuous-Time Versus Discrete-Time Dynamical Models 52  
        3.1.2 Digital Control Systems 53  
        3.1.3 Discrete-Time System Models for Control 55  
     3.2 Concluding Remarks 58  
     3.3 Notes and References 58  
     References 58  
  4 Parameter Adaptation Algorithms 59  
     4.1 Introduction 59  
     4.2 Structure of the Adjustable Model 60  
        4.2.1 Case (a): Recursive Configuration for System Identification---Equation Error 60  
        4.2.2 Case (b): Adaptive Feedforward Compensation---Output Error 62  
     4.3 Basic Parameter Adaptation Algorithms 64  
        4.3.1 Basic Gradient Algorithm 64  
        4.3.2 Improved Gradient Algorithm 67  
        4.3.3 Recursive Least Squares Algorithm 72  
        4.3.4 Choice of the Adaptation Gain 77  
        4.3.5 An Example 81  
     4.4 Stability of Parameter Adaptation Algorithms 82  
        4.4.1 Equivalent Feedback Representation of the Adaptive Predictors 83  
        4.4.2 A General Structure and Stability of PAA 86  
        4.4.3 Output Error Algorithms---Stability Analysis 90  
     4.5 Parametric Convergence 92  
        4.5.1 The Problem 92  
     4.6 The LMS Family of Parameter Adaptation Algorithms 96  
     4.7 Concluding Remarks 97  
     4.8 Notes and References 98  
     References 98  
  5 Identification of the Active Vibration Control Systems---The Bases 100  
     5.1 Introduction 100  
     5.2 Input--Output Data Acquisition and Preprocessing 102  
        5.2.1 Input--Output Data Acquisition Under an Experimental Protocol 102  
        5.2.2 Pseudorandom Binary Sequences (PRBS) 102  
        5.2.3 Data Preprocessing 104  
     5.3 Model Order Estimation from Data 105  
     5.4 Parameter Estimation Algorithms 107  
        5.4.1 Recursive Extended Least Squares (RELS) 109  
        5.4.2 Output Error with Extended Prediction Model (XOLOE) 111  
     5.5 Validation of the Identified Models 113  
        5.5.1 Whiteness Test 113  
     5.6 Concluding Remarks 115  
     5.7 Notes and References 116  
     References 116  
  6 Identification of the Test Benches in Open-Loop Operation 117  
     6.1 Identification of the Active Hydraulic Suspension in Open-Loop Operation 117  
        6.1.1 Identification of the Secondary Path 118  
        6.1.2 Identification of the Primary Path 123  
     6.2 Identification of the AVC System Using Feedback Compensation Through an Inertial Actuator 124  
        6.2.1 Identification of the Secondary Path 124  
        6.2.2 Identification of the Primary Path 130  
     6.3 Identification of the Active Distributed Flexible Mechanical Structure Using Feedforward--Feedback Compensation 131  
     6.4 Concluding Remarks 137  
     6.5 Notes and References 137  
     References 137  
  7 Digital Control Strategies for Active Vibration Control---The Bases 139  
     7.1 The Digital Controller 139  
     7.2 Pole Placement 141  
        7.2.1 Choice of HR and HS---Examples 142  
        7.2.2 Internal Model Principle (IMP) 144  
        7.2.3 Youla--Ku?era Parametrization 145  
        7.2.4 Robustness Margins 147  
        7.2.5 Model Uncertainties and Robust Stability 150  
        7.2.6 Templates for the Sensitivity Functions 152  
        7.2.7 Properties of the Sensitivity Functions 152  
        7.2.8 Input Sensitivity Function 155  
        7.2.9 Shaping the Sensitivity Functions for Active Vibration Control 157  
     7.3 Real-Time Example: Narrow-Band Disturbance Attenuation on the Active Vibration Control System Using an Inertial Actuator 161  
     7.4 Pole Placement with Sensitivity Function Shaping by Convex Optimisation 164  
     7.5 Concluding Remarks 167  
     7.6 Notes and References 167  
     References 168  
  8 Identification in Closed-Loop Operation 170  
     8.1 Introduction 170  
     8.2 Closed-Loop Output Error Identification Methods 171  
        8.2.1 The Closed-Loop Output Error Algorithm 175  
        8.2.2 Filtered and Adaptive Filtered Closed-Loop Output Error Algorithms (F-CLOE, AF-CLOE) 176  
        8.2.3 Extended Closed-Loop Output Error Algorithm (X-CLOE) 177  
        8.2.4 Taking into Account Known Fixed Parts in the Model 178  
        8.2.5 Properties of the Estimated Model 179  
        8.2.6 Validation of Models Identified in Closed-Loop Operation 180  
     8.3 A Real-Time Example: Identification in Closed-Loop and Controller Redesign for the Active Control System Using an Inertial Actuator 182  
     8.4 Concluding Remarks 186  
     8.5 Notes and References 186  
     References 187  
  9 Reduction of the Controller Complexity 188  
     9.1 Introduction 188  
     9.2 Criteria for Direct Controller Reduction 190  
     9.3 Estimation of Reduced Order Controllers by Identification in Closed-Loop 192  
        9.3.1 Closed-Loop Input Matching (CLIM) 192  
        9.3.2 Closed-Loop Output Matching (CLOM) 195  
        9.3.3 Taking into Account the Fixed Parts of the Nominal Controller 195  
     9.4 Real-Time Example: Reduction of Controller Complexity 197  
     9.5 Concluding Remarks 200  
     9.6 Notes and References 201  
     References 201  
  Part III Active Damping 202  
  10 Active Damping 203  
     10.1 Introduction 203  
     10.2 Performance Specifications 204  
     10.3 Controller Design by Shaping the Sensitivity Functions Using ƒ 208  
     10.4 Identification in Closed-Loop of the Active Suspension ƒ 211  
     10.5 Redesign of the Controller Based on the Model Identified in Closed Loop 212  
     10.6 Controller Complexity Reduction 214  
        10.6.1 CLOM Algorithm with Simulated Data 216  
        10.6.2 Real-Time Performance Tests for Nominal and Reduced Order Controllers 218  
     10.7 Design of the Controller by Shaping the Sensitivity Function with Band-Stop Filters 219  
     10.8 Concluding Remarks 224  
     10.9 Notes and References 225  
     References 226  
  Part IV Feedback Attenuation of Narrow-Band Disturbances 227  
  11 Robust Controller Design for Feedback Attenuation of Narrow-Band Disturbances 228  
     11.1 Introduction 228  
     11.2 System Description 229  
     11.3 Robust Control Design 231  
     11.4 Experimental Results 234  
        11.4.1 Two Time-Varying Tonal Disturbances 235  
        11.4.2 Attenuation of Vibrational Interference 237  
     11.5 Concluding Remarks 238  
     11.6 Notes and References 238  
     References 239  
  12 Direct Adaptive Feedback Attenuation of Narrow-Band Disturbances 240  
     12.1 Introduction 240  
     12.2 Direct Adaptive Feedback Attenuation of Unknown and Time-Varying ƒ 241  
        12.2.1 Introduction 241  
        12.2.2 Direct Adaptive Regulation Using Youla--Ku?era Parametrization 245  
        12.2.3 Robustness Considerations 247  
     12.3 Performance Evaluation Indicators for Narrow-Band Disturbance Attenuation 248  
     12.4 Experimental Results: Adaptive Versus Robust 251  
        12.4.1 Central Controller for Youla--Ku?era Parametrization 251  
        12.4.2 Two Single-Mode Vibration Control 251  
        12.4.3 Vibrational Interference 254  
     12.5 Adaptive Attenuation of an Unknown Narrow-Band Disturbance on the Active Hydraulic Suspension 256  
     12.6 Adaptive Attenuation of an Unknown Narrow-Band Disturbance on the Active Vibration Control System Using an Inertial Actuator 259  
        12.6.1 Design of the Central Controller 260  
        12.6.2 Real-Time Results 262  
     12.7 Other Experimental Results 264  
     12.8 Concluding Remarks 264  
     12.9 Notes and References 265  
     References 266  
  13 Adaptive Attenuation of Multiple Sparse Unknown and Time-Varying Narrow-Band Disturbances 269  
     13.1 Introduction 269  
     13.2 The Linear Control Challenge 269  
        13.2.1 Attenuation of Multiple Narrow-Band Disturbances Using Band-Stop Filters 271  
        13.2.2 IMP with Tuned Notch Filters 275  
        13.2.3 IMP Design Using Auxiliary Low Damped Complex Poles 276  
     13.3 Interlaced Adaptive Regulation Using Youla--Ku?era IIR Parametrization 277  
        13.3.1 Estimation of AQ 279  
        13.3.2 Estimation of BQ(q-1) 281  
     13.4 Indirect Adaptive Regulation Using Band-Stop Filters 285  
        13.4.1 Basic Scheme for Indirect Adaptive Regulation 286  
        13.4.2 Reducing the Computational Load of the Design Using the Youla--Ku?era Parametrization 287  
        13.4.3 Frequency Estimation Using Adaptive Notch Filters 288  
        13.4.4 Stability Analysis of the Indirect Adaptive Scheme 291  
     13.5 Experimental Results: Attenuation of Three Tonal Disturbances with Variable Frequencies 291  
     13.6 Experimental Results: Comparative Evaluation of Adaptive Regulation Schemes for Attenuation of Multiple Narrow-Band Disturbances 292  
        13.6.1 Introduction 292  
        13.6.2 Global Evaluation Criteria 297  
     13.7 Concluding Remarks 304  
     13.8 Notes and References 304  
     References 305  
  Part V Feedforward-Feedback Attenuation of Broad-Band Disturbances 307  
  14 Design of Linear Feedforward Compensation of Broad-band Disturbances from Data 308  
     14.1 Introduction 308  
     14.2 Indirect Approach for the Design of the Feedforward Compensator from Data 311  
     14.3 Direct Approach for the Design of the Feedforward Compensator from Data 311  
     14.4 Direct Estimation of the Feedforward Compensator and Real-Time Tests 315  
     14.5 Concluding Remark 321  
     14.6 Notes and References 321  
     References 322  
  15 Adaptive Feedforward Compensation of Disturbances 324  
     15.1 Introduction 324  
     15.2 Basic Equations and Notations 327  
     15.3 Development of the Algorithms 329  
     15.4 Analysis of the Algorithms 332  
        15.4.1 The Perfect Matching Case 332  
        15.4.2 The Case of Non-perfect Matching 334  
        15.4.3 Relaxing the Positive Real Condition 336  
     15.5 Adaptive Attenuation of Broad-band Disturbances---Experimental Results 337  
        15.5.1 Broad-band Disturbance Rejection Using Matrix Adaptation Gain 338  
        15.5.2 Broad-band Disturbance Rejection Using Scalar Adaptation Gain 342  
     15.6 Adaptive Feedforward Compensation with Filtering of the Residual Error 349  
     15.7 Adaptive Feedforward + Fixed Feedback Compensation of Broad-band Disturbances 351  
        15.7.1 Development of the Algorithms 353  
        15.7.2 Analysis of the Algorithms 355  
     15.8 Adaptive Feedforward + Fixed Feedback Attenuation of Broad-band Disturbances---Experimental Results 356  
     15.9 Concluding Remarks 358  
     15.10 Notes and References 358  
     References 359  
  16 Youla--Ku?era Parametrized Adaptive Feedforward Compensators 363  
     16.1 Introduction 363  
     16.2 Basic Equations and Notations 364  
     16.3 Development of the Algorithms 366  
     16.4 Analysis of the Algorithms 369  
        16.4.1 The Perfect Matching Case 369  
        16.4.2 The Case of Non-perfect Matching 370  
        16.4.3 Relaxing the Positive Real Condition 371  
        16.4.4 Summary of the Algorithms 371  
     16.5 Experimental Results 373  
        16.5.1 The Central Controllers and Comparison Objectives 373  
        16.5.2 Broad-band Disturbance Rejection Using Matrix Adaptation Gain 373  
        16.5.3 Broad-band Disturbance Rejection Using Scalar Adaptation Gain 376  
     16.6 Comparison of the Algorithms 378  
     16.7 Concluding Remarks 380  
     16.8 Notes and References 380  
     References 380  
  Appendix A Generalized Stability Margin and Normalized Distance Between Two Transfer Functions 382  
  Appendix B Implementation of the Adaptation Gain Updating---The U-D Factorization 386  
  Appendix C Interlaced Adaptive Regulation: Equations Development and Stability Analysis 388  
  Appendix D Error Equations for Adaptive Feedforward Compensation 392  
  Appendix E ``Integral + Proportional'' Parameter Adaptation Algorithm 399  
  Index 404  


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