本論文之主旨係在於發展適應性強健型小腦模型控制器，其並結合適應性控制、與強健控制等理論，再依據李雅普諾夫穩定性定理設計小腦模型控制器的參數適應性調整法則，因此整個閉迴路控制系統的穩定性可以被保證。最後並廣泛的應用在一些具有非線性且不確定系統之閉迴路控制上。本論文將探討所提出來的適應性強健型小腦模型控制器及其應用性。首先，將介紹小腦模型控制器，接著具有最佳學習速率的小腦模型控制器將針對單輸入-單輸出的高壓電力供應系統。在多輸入-多輸出控制系統方面，本論文針對系統分別提出不需數學模型及需要數學模型之控制法則。這些控制法則分別採用強健型小腦模型控制器為主控制器，所開發出來的多輸入-多輸出適應性強健型小腦模型控制器並應用於解決一些具有高度非線性且時變系統的軌跡追蹤問題，例如混沌系統。經由模擬與實作的結果顯示，對於這些具有不確定量且非線性之系統，本論文所提出的控制系統均能達到令人滿意的控制性能。

The purpose of this thesis is to develop the adaptive robust cerebellar model articulation controller (CMAC) system by integrating CMAC with adaptive control and robust control technologies for the control application to uncertain nonlinear systems. According to Lyapunov synthesis approach, the adaptive tuning laws of CMAC can be derived and the system stability can be guaranteed. This thesis introduces the structures of CMAC first. Then, CMAC with optimal learning rate is developed for the single-input single-output (SISO) high voltage power supply (HVPS) system. Moreover, this thesis also proposes the robust CMAC control systems for the uncertain nonlinear MIMO systems. In this design, the developed multi-input multi-output (MIMO) control system is then applied to a nonlinear chaotic system. From the simulation results, the control schemes proposed in this thesis have been shown to achieve satisfactory control performance for the considered nonlinear systems.

書名頁 i
論文口試委員審定書 ii
授權書 iii
摘要 iv
Abstract v
致謝 vi
Contents vii
List of Tables ix
List of Figures x
Nomenclature xiii

Chapter 1 Introduction 1

Chapter 2 Adaptive CMAC Design with Optimal Learning Rate
for High Voltage Power Supply
2.1 Introduction of CMAC 3
2.2 Controller design of power converter 8
2.2.1 Problem formulation
2.2.2 General cerebella model articulation neural network 9
2.2.3 Learning algorithm 11
2.3 Stability analysis 13
2.4 HVPS Model 19
2.4.1 Buck DC-DC converter model 19
2.4.2 Modeling of high voltage power converter 22
2.4.3 Transfer function of PWM 24
2.5 Simulation result for HVPS 24

Chapter 3 Robust CMAC Control for MIMO Nonlinear Systems
3.1 Problem formulation 38
3.2 Robust controller design 40
3.3 Simulation result 47

Chapter 4 Conclusion and Suggestion for Future Research
4.1 Conclusions 62
4.2 Suggestion for future research 62
Reference 64
Autobiography 72

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