Linear and Nonlinear Iterative Learning Control (Lecture Notes in Control and Information Sciences (291))

This monograph summarizes the recent achievements made in the field of iterative learning control. The book is self-contained in theoretical analysis and can be used as a reference or textbook for a graduate level course as well as for self-study. It opens a new avenue towards a new paradigm in deterministic learning control theory accompanied by detailed examples. Linear and Nonlinear Iterative Learning Control......Page 4 Content......Page 8 Preface ......Page 6 1.1 What is Iterative Learning Control......Page 26 1.1.1 The Simplest ILC: An Example......Page 29 1.1.2 ILC for Non-affine Process......Page 31 1.1.3 ILC for Dynamic Process......Page 32 1.1.4 D-Type ILC for Dynamic Process......Page 36 1.1.5 Can We Relax the Identical Initialization Condition?......Page 38 1.1.6 Why ILC......Page 39 1.2 History of ILC......Page 41 1.3 Book Overview......Page 42 2.1 Introduction......Page 45 2.2 Problem Formulation......Page 46 2.3 Convergence Properties in Iteration Domain......Page 48 2.4 Robust Optimal Design for Convergence Speed......Page 51 2.5 Robust Design for Global Uniform Bound......Page 54 2.6 Monotonic Covergence Interval......Page 57 2.7 Illustrative Examples......Page 58 2.8 Conclusions......Page 61 3.1 Introduction......Page 63 3.2 Preliminary......Page 64 3.3 Convergence Speed Analysis of the Second Order ILC......Page 66 3.4 m-th Order ILC......Page 69 3.6 Conclusions......Page 75 4.2 Preliminary......Page 77 4.3 Problem Formulation......Page 78 4.4 The Linear-Type ILC Approach......Page 80 4.5 Robust Optimal Design for MIMO Dynamic Systems......Page 82 4.6 Illustrative Example......Page 88 4.7 Conclusions......Page 90 5.1 Introduction......Page 92 5.2 Problem Statement......Page 93 5.3 Convergence Analysis for Linear-Type ILC Scheme......Page 94 5.4 The Newton-Type ILC Scheme......Page 96 5.5 The Secant-Type ILC Scheme......Page 100 5.7 Conclusions......Page 103 6.2 Preliminary......Page 105 6.3 The Newton-Type ILC Approach......Page 108 6.4 The Secant-Type ILC Approach......Page 110 6.5 Illustrative Example......Page 115 6.6 Conclusions......Page 116 7.1 Introduction......Page 117 7.2 From Contraction Map to Energy Function Approach......Page 118 7.2.1 ILC Bottleneck - GLC......Page 119 7.2.2 What Can We Learn From Adaptive Control......Page 121 7.2.3 ILC with Composite Energy Function......Page 123 7.3 Gerneral Problem Formulation......Page 127 7.4 Learning Control Configuration and Convergence Analysis......Page 129 7.5 Illustrative Example......Page 134 7.6 Conclusions......Page 135 8.1 Introduction......Page 137 8.2 Problem Formulation......Page 138 8.3 Nonlinear Optimal Control......Page 139 8.4. Sythesized Quasi-Optimal Learning Control Scheme......Page 140 8.5 Illustrative Example......Page 145 8.6 Conclusions......Page 147 9.1 Introduction......Page 150 9.2 Fundamentals of Wavelet Networks......Page 151 9.3.1 Problem Formulation......Page 153 9.3.2 Design and Analysis of LWC......Page 156 9.4.1 Problem Formulation......Page 163 9.4.2 LWC Design and Analysis......Page 165 9.5 Illustrative Examples......Page 168 9.6 Conclusions......Page 174 10.1 Conclusions......Page 175 10.2 Recommendation for Future Research......Page 176 1. Introduction -- 2. Robust Optimal Design For The First Order Linear-type Ilc Scheme -- 3. Analysis Of Higher Order Linear-type Ilc Schemes -- 4. Linear Ilc Design For Mimo Dynamic Systems -- 5. Nonlinear-type Ilc Schemes -- 6. Nonlinear Ilc Design For Mimo Dynamic Systems -- 7. Composite Energy Function Based Learning Control -- 8. Quasi-optimal Iterative Learning Control -- 9. Learning Wavelet Control Using Constructive Wavelet Networks -- 10. Conclusions And Recommendation -- A. Appendix. Jian-xin Xu, Ying Tan. Includes Bibliographical References (p. [163]-171) And Index.