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研究生:楊中天
研究生(外文):Chune-Tine Yang
論文名稱:感應馬達驅動系統之適應性遞迴小波小腦模型控制器設計
論文名稱(外文):Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Drive Systems
指導教授:王順源王順源引用關係
口試委員:周仁祥曾煥雯宋文財曾傳蘆
口試日期:2014-07-24
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:145
中文關鍵詞:Takagi-Sugeno-Kang模糊系統遞迴小波小腦模型控制器向量控制直接轉矩控制
外文關鍵詞:Vector ControlTakagi-Sugeno-Kang Fuzzy SystemDirect Torque ControlRecurrent Wavelet Cerebellar Model Articulation Controller
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本文結合遞迴小腦模型控制器及適應性理論並以小波函數為基底函數,設計出適應性遞迴小波小腦模型控制器(adaptive recurrent wavelet cerebellar model articulation controller, ARWCMAC)。本文提出的ARWCMAC比傳統的小腦模型控制器有更好的學習率以及動態響應。此外,權重更新式學習可使追蹤的速度誤差快速收斂。使用Lyapunov來決定ARWCMAC的學習規則,使此控制器在系統上是穩定的。
本文提出的速度控制器整合了模糊轉矩和磁通控制器、模糊定子電阻估測器於感應馬達直接轉矩控制(direct torque control, DTC),且本文所提出的速度控制器整合了Takagi-Sugeno (T-S) 模糊磁通估測器與適應性Takagi-Sugeno-Kang (TSK) 模糊定轉子電阻估測器、TSK模糊轉速估測器於感應馬達磁場導向控制(field oriented control, FOC)。
最後,本文提出的速度控制器分別結合了直接轉控制架構以及磁場導向控制架構。經模擬結果證明,在馬達負載轉矩為8 Nm,轉速控制範圍在36 rpm至2000 rpm時,所提出方法皆具有優異的轉速動態響應。


In this study, the adaptive recurrent wavelet cerebellar model articulation controller (ARWCMAC) is proposed, which is designed based on the adaptive control theory and the Recurrent Cerebellar Model Articulation controller (CMAC) with wavelet basis function. The proposed ARWCMAC has superior capability to the conventional cerebellar model articulation controller in efficient learning mechanism and dynamic response. Furthermore, the variable optimal learning-rates are derived to achieve the fastest convergence of tracking speed error. The analytical method based on a Lyapunov function is proposed to determine the learning rates of ARWCMAC, so that the stability of the system can be guaranteed.
This proposed speed controller integrated FTC, FFC and FSRE for DTC of induction motor, and use an ARWCMAC integrated T-S fuzzy flux estimator, TSK rotor resistance estimator and TSK estimator for FOC of induction motor.
Finally, this propose speed controller integrated DTC, FOC structure for induction motor.Acording to the simuliaton, the proposed direct torque control systems have excellent speed response and robustness within 36 rpm to 2000 rpm during 8 Nm load torque.


中文摘要 i
英文摘要 ii
誌 謝 iv
目 錄 v
表 目 錄 ix
圖 目 錄 x
第一章 緒論 1
1.1 研究動機與目的 1
1.2 文獻探討 2
1.3 論文大綱 4
第二章 感應電動機驅動控制理論 5
2.1 前言 5
2.2 感應電動機數學模型 6
2.3 轉子磁場導向控制 9
2.3.1 轉子磁場導向控制原理 9
2.4 直接轉矩控制 12
2.4.1 直接轉矩控制原理 12
2.5電壓空間向量調變技術 14
2.6速度估測器設計 18
2.7 本章結論 20
第三章 模糊控制理論 21
3.1 前言 21
3.2 模糊理論基本原理 21
3.3 模糊控制系統設計 22
3.3.1 模糊化機構 23
3.3.2 模糊知識庫 25
3.3.3 模糊推論引擎 26
3.3.4 解模糊化機構 27
3.4 模糊集合基本運算 28
3.5 Takagi-Sugeno-Kang模糊系統 31
3.6 Takagi-Sugeno模糊系統 32
3.7 本章結論 35
第四章 小腦模型控制器理論 36
4.1 前言 36
4.2 小腦模型控制器 36
4.2.1 小腦模型控制器架構 37
4.2.2 小腦模型控制器之運作過程 38
4.2.2.1 輸入狀態層映射至聯想記憶體層 39
4.2.2.2 聯想記憶體層映射至真實記憶體層 40
4.2.2.3 真實記憶體層至輸出層 42
4.2.3 小腦模型控制器學習運算法則 44
4.3 小腦模型控制器特性 44
4.4 遞迴小波小腦模型控制器原理及設計 45
4.4.1 小波函數介紹 45
4.4.2 遞迴小波小腦模型控制器架構 46
4.5 遞迴小波小腦模型控制器模擬 47
4.6 本章結論 50
第五章 控制器與估測器設計 51
5.1 前言 51
5.2 轉速控制器設計 51
5.2.1 適應性遞迴小波小腦模型控制器 51
5.2.1.1 適應性遞迴小波小腦模型控制器設計 52
5.2.1.2 適應性更新法則之推導 55
5.2.1.3 適應性遞迴小波小腦控制器之穩定度分析 57
5.3 T-S模糊轉子磁通估測器設計 58
5.3.1 轉子磁通估測器 59
5.3.2 電流型磁通估測器 64
5.4 模糊轉矩控制 66
5.5 T-S模糊磁通控制 72
5.6 定轉子電阻估測器 75
5.6.1適應性TSK模糊定轉子電阻估測器 75
5.6.2模糊定子電阻估測器 79
5.7 本章結論 82
第六章 感應馬達驅動系統模擬 83
6.1 適應性遞迴小波小腦模型控制器模擬 83
6.1.1 感應電動機磁場導向控制系統模擬 83
6.1.2 感應電動機直接轉矩控制系統模擬 113
6.2 模擬結果討論 133
6.3 本章結論 134
第七章 結論與未來研究方向 135
7.1 結論 135
7.2 未來研究方向 136
參考文獻 137
符號彙編 142
作者簡介 145


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