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研究生： 杜彥頤
Du, Yan-Yi
論文名稱： 適用於大尺度系統之分散式軌跡追蹤器:反覆學習與數位重新設計方法
Decentralized Trajectory Trackers for Large-Scale Systems: Iterative Learning and Digital Redesign Approaches
指導教授： 蔡聖鴻
Tsai, Sheng-Hong Jason
學位類別： 博士
Doctor
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2011
畢業學年度： 99
語文別： 英文
論文頁數： 179
中文關鍵詞： 反覆學習控制 、反飽和機制 、分散式軌跡追蹤器 、數位重新設計
外文關鍵詞： Iterative learning control, anti-windup scheme, decentralized trajectory tracker, digital redesign
相關次數： 點閱：138  下載：2 
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    • 針對有/無輸入限制的大尺度資料取樣系統，本論文藉由數位重新設計技術提出反覆學習型分散式軌跡追蹤器，以達到良好的追蹤效果與閉迴路解耦特性。其研究主題陳述如下：首先，針對複雜的非線性系統，提出一個具有進化演算法調整的觀測型反覆學習控制器，以克服傳統反覆學習控制在學習收斂性、收斂速度與其典型限制「初始值一致性」的問題。接著，考慮具有輸入限制的線性系統，提出一個含有間接學習機制的最佳化反飽和式追蹤器，以解決高增益最佳化追蹤器之輸入飽和問題。藉由權重因子的調整，本文所提反飽和機制可避免複雜的數值運算且盡可能在不損耗追蹤效果情況下，精準調整控制輸入以符合規格限制。再者，針對由多個互聯子系統所組成的大尺度系統之控制問題，提出具有串接式反覆學習機制且以參考模型為基礎的分散式適應性追蹤器，以同時獲得強健的解耦特性與良好的追蹤效果。最後，考慮具有輸入限制與狀態延遲的大尺度未知聯結系統，運用離線式估測器/卡爾曼濾波器鑑別法則來決定適當低階的獨立式模型與估測器，且配合前述的反飽和機制以建構分散式軌跡追蹤器。在本論文中，以多個例題來說明所提方法之有效性。

    Via the digital redesign technique, this dissertation proposes iterative learning-based decentralized trajectory trackers for large-scale sampled data systems with/without input constraints to obtain good tracking performances and a closed-loop decoupling property. The major research topics of this dissertation are stated as follows: Firstly, an observer-based iterative learning control (ILC) scheme with evolutionary programming is proposed to resolve some problems of a traditional ILC on learning convergence, convergence speed, and the typical limitation, identical initial condition (i.i.c.), for complicated nonlinear systems. Secondly, for linear input constrained systems, an optimal anti-windup tracker with an indirect iterative learning scheme is presented to resolve the input saturation problem of a high-gain optimal tracker. Avoiding the complex numerical calculation, the proposed anti-windup scheme by adjusting a weighted factor can precisely regulate the control input to satisfy the specified restriction without losing the good tracking performance as possible. Thirdly, to deal with the control problem of large-scale systems consisting N interconnected subsystems, a model-reference-based decentralized adaptive tracker with a cascade iterative learning scheme is developed to simultaneously obtain the robust decoupling property in time domain and the good tracking performance in iterative domain. Finally, applying off-line observer/Kalman filter identification (OKID) determines appropriate (low-)orders of the independent models/observers, and then adopting the proposed anti-windup scheme according to these models establishes decentralized trajectory trackers for unknown interconnected large-scale systems with input constraints and state delay. Some illustrative examples are given to demonstrate the effectiveness of the proposed methodologies.

    中文摘要 i Abstract ii Acknowledgement iii Contents iv List of Tables vii List of Figures viii Symbols and Abbreviations xiii Chapter 1 Introduction 1 1.1 Literature survey 2 1.1.1 Iterative learning control 2 1.1.2 Anti-windup control 5 1.1.3 Decentralized control 6 1.1.4 Digital redesign 7 1.2 Dissertation overview 8 Chapter 2 Observer-Based Iterative Learning Control for MIMO Nonlinear Systems 11 2.1 Introduction 12 2.2 Linear quadratic regulator-based observer for nonlinear systems 14 2.2.1 Linear quadratic regulator-based observer design 14 2.2.2 Optimal linearization algorithm 16 2.3 Observer-based iterative learning control 18 2.3.1 Iterative learning control problem 18 2.3.2 Iterative learning control with LQR-based observer 21 2.3.3 Convergence analysis of OB-ILC 23 2.4 Improved OB-ILC tracker via evolutionary programming 27 2.4.1 Quasi-random sequences (QRS) 28 2.4.2 The procedure for evolutionary programming 30 2.5 Other improved issues of the ILC tracker 34 2.5.1 Initialization of the control input for the ILC tracker 34 2.5.2 Modified learning rule for robot manipulator 34 2.5.3 Resolution of initial shift problem for OB-ILC 36 2.6 Design procedure of observer-based EP-ILC for nonlinear systems 38 2.7 Illustrative examples 42 2.8 Summary 47 Chapter 3 Iterative Learning-Based Anti-windup Tracker for MIMO Systems under Input Constraint 49 3.1 Introduction 50 3.2 Modified optimal linear control 52 3.2.1 Motivation of the modified optimal control scheme 52 3.2.2 Characteristic of the modified control scheme 55 3.2.3 Iterative learning-based anti-windup scheme 60 3.2.4 Detailed procedure of the modified LQAT design 64 3.3 Digital redesign of optimal control for sampled-data systems under input constraints 67 3.4 An illustrative example 74 3.5 Summary 91 Chapter 4 Iterative Learning-Based Decentralized Adaptive Tracker for Large-Scale System 93 4.1 Introduction 94 4.2 Model reference decentralized adaptive control 96 4.2.1 Decentralized reference model 96 4.2.2 Strictly decentralized controller design 98 4.3 Digital redesign of decentralized adaptive control system 101 4.3.1 Digital redesign methodology 101 4.3.2 Digitally redesigned model-reference-based decentralized adaptive controller 106 4.4 Evolutionary programming-based iterative learning control 111 4.4.1 Discrete iterative learning control 111 4.4.2 Improved ILC via evolutionary programming 114 4.5 Summaries of the proposed design procedure 116 4.6 An illustrative example 117 4.7 Summary 125 Chapter 5 OKID-Based Decentralized Anti-windup Tracker for Unknown Interconnected Large-Scale System 127 5.1 Introduction 128 5.2 OKID-based decentralized modeling and control 130 5.3 Observer/Kalman filter identification 133 5.3.1 Basic observer equation 133 5.3.2 Computation of Markov parameters 136 5.3.2-1 System Markov parameters 136 5.3.2-2 Observer gain Markov parameters 136 5.3.3 Eigensystem realization algorithm 136 5.3.4 Relationship to a Kalman Filter 139 5.4 Digital redesign of observer-based anti-windup tracker 140 5.4.1 Observer-based modified LQAT design 141 5.4.2 Digital redesign of the observer-based modified LQAT 144 5.5 Design procedure 146 5.6 An illustrative example 147 5.7 Summary 159 Chapter 6 Conclusions 160 6.1 Conclusions 160 6.2 Future research directions 162 Appendix A 163 References 166 Biography 177 Publication List 178

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