中文摘要
本論文主要目的在於發展小波類神經網路控制系統以及強健性小波類神經網路滑動模式控制系統，並應用於旋轉型感應伺服馬達精密定位控制上。首先將小波理論融入傳統的類神經網路中，發展成為小波類神經網路，利用誤差倒傳遞演算法則作為線上參數調整依據，並根據離散式里亞普諾穩定理論作收斂分析以推導獲得適應性學習速率。由於小波類神經網路控制系統具有強大的學習能力，因此整個控制系統設計不需要約束條件和受控系統資訊，然而此小波類神經網路控制系統無法保證整個控制系統穩定特性。因此引進具積分形式之滑動平面的全域滑動模式控制系統，此方式特點在於不具傳統滑動模式控制所需的迫近模式以降低系統不確定量所造成之影響。為了解決全域滑動模式控制系統之不確定量邊界值選取問題，進而引進小波類神經網路滑動模式控制系統，作為感應伺服馬達定位控制法則，以小波類神經網路線上估測不確定量邊界值，但其控制力存在嚴重顫抖現象，故提出強健性小波類神經網路滑動模式控制系統來消除控制力顫抖現象，此系統最主要是將邊界層的概念引入全域滑動模式控制系統中，而小波類神經網路則運用在線上估測邊界層寬度以及不確定量邊界值。最後本論文利用數值模擬和實作結果佐證所設計之控制系統應用於旋轉型感應伺服馬達定位控制上之有效性與強健性。

目錄
中文摘要Ⅰ
英文摘要Ⅱ
致謝Ⅲ
目錄Ⅳ
第一章緒論1
1.1研究動機與目的1
1.2控制問題簡介2
1.3控制方法簡介2
1.4論文大綱6
第二章小波類神經網路8
2.1前言8
2.2小波理論簡介8
2.3類神經網路概述13
2.4小波類神經網路的描述19
第三章小波類神經網路控制系統23
3.1前言23
3.2感應伺服馬達動態模型23
3.3小波類神經網路25
3.4線上學習機制26
3.5小波類神經網路收斂性分析28
第四章強健性小波類神經網路滑動模式控制系統34
4.1前言34
4.2全域滑動模式控制系統35
4.2.1基礎模型設計36
4.2.2約束控制器設計37
4.3小波類神經網路滑動模式控制系統39
4.4強健性小波類神經網路滑動模式控制系統43
第五章數值模擬與實作結果48
5.1感應伺服馬達驅動系統48
5.2實驗裝置49
5.3小波類神經網路控制系統應用52
5.3.1數值模擬53
5.3.2實作結果54
5.4強健性小波類神經網路滑動模式控制系統應用56
5.4.1數值模擬57
5.4.2實作結果63
第六章結論71
參考文獻73
作者簡歷80

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