Learning-based Adaptive Control: An Extremum Seeking Approach - Theory and Applications presents comprehensive information on Adaptive Control for optimal action based on the current characteristics of a system, also presenting tactics on how to learn how characteristics change along the way. The bo
Learning-Based Adaptive Control: An Extremum Seeking Approach ? Theory and Applications
β Scribed by Benosman, Mouhacine
- Publisher
- Elsevier Science
- Year
- 2016
- Tongue
- English
- Leaves
- 277
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Cover......Page 1
LEARNING-BASEDADAPTIVECONTROL:An Extremum SeekingApproach - Theory andApplications......Page 3
Copyright......Page 4
Preface......Page 5
References......Page 8
Acknowledgments......Page 9
Norms Definitions and Properties......Page 10
Vector Functions and Their Properties......Page 13
Stability of Dynamical Systems......Page 16
Exact Input-Output Linearization by Static-State Feedback and the Notion of Zero Dynamics......Page 22
Geometric, Topological, and Invariance Set Properties......Page 25
References......Page 26
Introduction......Page 27
Adaptive Control Problem Formulation......Page 30
Linear Direct Model-Based Adaptive Control......Page 31
Nonlinear Direct Model-Based Adaptive Control......Page 35
Linear Indirect Model-Based Adaptive Control......Page 40
Nonlinear Indirect Model-Based Adaptive Control......Page 42
Model-Free Adaptive Control......Page 46
Learning-Based Adaptive Control......Page 50
Conclusion......Page 55
References......Page 56
Introduction......Page 62
Class of Systems......Page 65
Step One: Robust Control Design......Page 66
Step Two: Iterative Auto-Tuning of the Feedback Gains......Page 70
Robust Controller......Page 76
Learning-Based Auto-Tuning of the Controller Gains......Page 79
Simulation Results......Page 80
System Modeling......Page 92
Robust Controller......Page 97
Learning-Based Auto-Tuning of the Feedback Gains......Page 98
Simulations Results......Page 99
Conclusion and Discussion of Open Problems......Page 100
References......Page 106
Introduction......Page 108
Basic Notations and Definitions......Page 110
ES-Based Indirect Adaptive Controller forthe Case of General Nonlinear Models WithConstant Model Uncertainties......Page 113
ES-Based Indirect Adaptive Controllerfor General Nonlinear Models With Time-Varying Model Uncertainties......Page 116
The Case of Nonlinear Models Affinein the Control......Page 118
Nominal Controller......Page 119
Lyapunov Reconstruction-Based ISS Controller......Page 121
MES-Based Parametric Uncertainties Estimation......Page 124
Controller Design......Page 127
Numerical Results......Page 129
The Case of Two-Link Rigid Manipulators......Page 135
MES-Based Uncertainties Estimation......Page 137
Conclusion......Page 144
References......Page 145
Introduction......Page 148
Basic Notations and Definitions......Page 151
Problem Formulation......Page 152
Open-Loop Parameters Estimation......Page 153
ES-Based Closed-Loop Parametric Identification for Nonlinear Systems......Page 156
Problem Formulation......Page 157
Parametric Estimation in the Case of Nonlinear Systems Affine in the Control......Page 159
Case 1......Page 162
Case 2......Page 165
Identification and Stable PDEs' ModelReduction by ES......Page 167
ES-Based ROM Parameters' Identification......Page 170
POD Basis Functions......Page 171
MES-Based Open-Loop Parameters' Estimation for PDEs......Page 173
Different Closure Models for ROM Stabilization......Page 176
MES-Based Closure Models' Auto-Tuning......Page 179
Electromagnetic Actuator......Page 188
Robot Manipulator With Two Rigid Arms......Page 194
The Coupled Burgers' PDE......Page 197
Burgers' Equation ES-Based Parameters' Estimation......Page 198
Burgers' Equation ES-Based POD ROM Stabilization......Page 206
Conclusion and Open Problems......Page 222
References......Page 225
Introduction......Page 229
Problem Formulation......Page 234
Tightening the Constrains......Page 236
Invariant Set for Tracking......Page 237
MPC Problem......Page 238
DIRECT-Based Iterative Learning MPC......Page 239
Proof of the MPC ISS-Guarantee and the Learning Convergence......Page 241
Constrained Linear Nominal MPC......Page 244
MES-Based Adaptive MPC Algorithm......Page 245
Stability Discussion......Page 247
Example for the DIRECT-Based ILC MPC......Page 249
Example for the Dither-Based ESILC-MPC......Page 250
Conclusion and Open Problems......Page 255
References......Page 258
Conclusions and Further Notes......Page 261
References......Page 268
D......Page 271
F......Page 272
L......Page 273
N......Page 274
S......Page 275
V......Page 276
Back Cover......Page 277
β¦ Subjects
Adaptive control systems;Systèmes adaptatifs;Ressources Internet
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