本文主要發展以全域滑動模式理論為基礎之直流-直流升壓式轉換器電壓調節控制設計。首先，全域滑動模式控制架構被用來設計於直流-直流升壓式轉換器之電壓追蹤控制，此控制方法是基於李亞普諾穩定理論而發展，使系統性能在整個控制的過程中，不受系統不確定量所影響且其沒有傳統滑動模式控制器的迫近模態，也就是在整個控制的過程中，其系統軌跡都將落在所規劃的滑動平面上。本文所設計全域滑動模式控制器經由數值模擬與實作結果驗證其不論是暫態性能或對於系統不確定量干擾的強健性都優於傳統的比例-積分控制器與傳統滑動模式控制器。另外，為了減輕來自於全域滑動模式控制法則之符號函數所產生的控制力抖動現象，同時也欲減小控制器對系統模型參數的依賴性，本文更進一步提出適應性模糊類神經網路控制器用來學習全域滑動模式的控制行為，藉由以李亞普諾穩定理論與投影法則推導出線上學習規則，使得適應性模糊類神經網路控制系統的穩定性可以獲得確保，且其控制力更可以直接應用於直流-直流升壓式轉換器之開關責任週期上，無需如傳統滑動模式控制器需受到嚴格的參數選擇限制。透過適應性模糊類神經網路控制器與全域滑動模式控制器的數值模擬與實作結果性能比較，可驗證適應性模糊類神經網路控制器的可行性且其控制性能確實優於全域滑動模式控制器。

This thesis focuses on the design of voltage regulation control for a dc-dc boost converter based on total sliding-mode theory. A total sliding-mode control (TSMC) scheme is firstly designed for the voltage tracking control of a conventional dc-dc boost converter. This control strategy is derived in the sense of Lyapunov stability theorem such that the stable tracking performance can be ensured under the occurrence of system uncertainties. The salient feature of this control scheme is that the controlled system has a total sliding motion without a reaching phase as in convenventional sliding-mode control (CSMC). Moreover, the effectiveness of the proposed TSMC scheme is verified by numerical simulations and realistic experimentations, and the advantages of good transient response and robustness to uncertainties are indicated in comparison with a conventional proportional-integral control (PIC) system and a CSMC scheme. In order to control the system more efficiency, a new TSMC control (NTSMC) scheme is presented. However, the chattering phenomena caused by the sign function is still existed in the NTSMC design and control parameter constraints are required. For the purpose of solving chattering phenomena and reducing the dependence on detailed system dynamics, an adaptive fuzzy-neural-network control (AFNNC) scheme is further designed to imitate the NTSMC law for the boost converter. In the AFNNC scheme, on-line learning algorithms are derived in the sense of Lyapunov stability theorem and projection algorithm to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The output of the AFNNC scheme can be easily supplied to the duty cycle of the power switch in the boost converter without strict constraints on control parameters selection in conventional control strategies. In addition, the effectiveness of the proposed AFNNC scheme is verified by numerical simulations and realistic experimentations, and its advantages are indicated in comparison with the NTSMC strategy.

書名頁 I
論文口試委員審定書 II
授權書 III
中文摘要 IV
Abstract VI
誌謝 VIII
Contents IX
List of Figures XI
List of Tables XIII
Chapter 1 Introduction 1
Chapter 2 System Descriptions 6
2.1 Overview 6
2.2 Auxiliary power module 7
2.3 Digital signal processor 7
2.4 Driving circuits 8
2.5 Feedback sensing circuits 9
2.6 Boost converter power stage 9
2.7 Mathematical model of boost converter 10
Chapter 3 Total Sliding-Mode Control System 13
3.1 Overview 13
3.2 Total sliding-mode control 13
3.2.1 Baseline model design 14
3.2.2 Curbing controller design 15
3.3 Numerical simulations and experimental results 18
3.3.1 Numerical simulations 21
3.3.2 Experimental results 29
3.4 Conclusions 36
Chapter 4 Adaptive Fuzzy-Neural-Network Control System 38
4.1 Overview 38
4.2 Dynamic model modification 38
4.2.1 System error dynamic 39
4.2.2 NTSMC control law 40
4.3 Adaptive fuzzy-neural-network control 44
4.4 Numerical simulations and experimental results 52
4.4.1 Numerical simulations 55
4.4.2 Experimental results 63
4.5 Conclusions 71
Chapter 5 Discussions and Suggestions for Future Research 73
5.1 Discussions 73
5.2 Suggestions for future research 74
References 76
Biographical Sketch 80
Publication List 81

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