利用遞迴式勒壤得模糊類神經網路於永磁輔助同步磁阻馬達驅動系統之智慧型計算轉矩控制

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洪崇祐(Chung-Yu Hung) 查詢紙本館藏

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電機工程學系

論文名稱

利用遞迴式勒壤得模糊類神經網路於永磁輔助同步磁阻馬達驅動系統之智慧型計算轉矩控制
(Intelligent Computed Torque Control of Permanent Magnet Assisted Synchronous Reluctance Motor Using Recurrent Legendre Fuzzy Neural Network)

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至系統瀏覽論文 (2027-8-1以後開放)

摘要(中)

本論文研究目的為研製與發展高性能永磁輔助同步磁阻馬達驅動系統，提出利用遞迴式勒壤得模糊類神經網路之計算轉矩控制法，以應對其非線性和時變特性。本論文首先介紹了使用有限元素分析法分析每安培最大轉矩控制，以獲得最佳的電流角命令，並將結果藉由查表法做應用。接著介紹計算轉矩控制法來追隨速度命令，但因系統存在總集不確定項很難事先得知，實際應用中難以實現。有鑒於此，提出結合了遞迴式勒壤得模糊類神經網路來近似計算轉矩控制。此外，為了補償遞迴式勒壤得模糊類神經網路可能的近似誤差，增加了一個自適應補償器，並利用李亞普諾夫穩定性理論推導，以保證遞迴式勒壤得模糊類神經網路線上學習法為漸進穩定。最後通過實驗結果驗證了所提出的遞迴式勒壤得模糊類神經網路之智慧型計算轉矩控制的有效性和強健性。
最後，本研究以32位元浮點運算數位訊號處理器TMS320F28075將所提出的智慧型控制實現於永磁輔助同步磁阻馬達驅動系統。

摘要(英)

An intelligent computed torque control using recurrent Legendre fuzzy neural network (ICTCRLFNN) is proposed in this study to construct a high-performance PMASynRM drive system to confront its nonlinear and time-varying control characteristics. First, the dynamic model of a maximum torque per ampere (MTPA) controlled PMASynRM drive using ANSYS Maxwell-2D is introduced. The results of the finite element analysis (FEA) are made into a lookup table (LUT) to generate the current angle command of the MTPA. Then, a computed torque control (CTC) system is designed for the tracking of the speed reference. Since the detailed system dynamics including the uncertainty of PMASynRM drive system is unavailable in advance, it is very difficult to design an effective CTC in practical applications. Therefore, to alleviate the existed difficulties of the CTC, a recurrent Legendre fuzzy neural network (RLFNN) is proposed in this study to approximate the CTC. In addition, to compensate the possible approximated error of the RLFNN, an adaptive compensator is augmented. The online learning algorithms of the RLFNN are derived by using the Lyapunov stability method to assure asymptotical stability. Finally, the effectiveness and robustness of the proposed ICTCRLFNN controlled PMASynRM drive are verified by some experimental results.
Finally, the proposed intelligent control system and the vector mechanism for the PMASynRM drive are implemented using a 32-bit floating point digital signal processor (DSP) TMS320F28075.

關鍵字(中)

★ 永磁輔助同步磁阻馬達
★ 計算轉矩控制
★ 遞迴式勒壤得模糊類神經網路
★ 每安培最大轉矩
★ 有限元素分析

關鍵字(英)

★ permanent magnet assisted synchronous reluctance motor (PMASynRM)
★ computed torque control (CTC)
★ recurrent Legendre fuzzy neural network (RLFNN)
★ maximum torque per ampere (MTPA)
★ finite element analysis (FEA)

論文目次

摘要 I
Abstract II
目錄 IV
圖目錄 VII
表目錄 XI
第一章緒論 1
1.1 研究動機與目的 1
1.2 文獻回顧 3
1.3 論文貢獻 6
1.4 論文大綱 7
第二章永磁輔助同步磁阻馬達之控制板介紹驅動系統之控制板介紹 8
2.1 前言 8
2.2 TMS320F28075數位訊號處理器簡介 11
2.3 功率級系統建構 12
2.3.1 前言 12
2.3.2 電容版設計 13
2.3.3 主功率級設計 14
2.3.4 閘級驅動設計 15
2.3.5 雙脈衝電路工作原理與結果分析 16
2.4 TMS320F28075數位訊號處理器控制板之電路 17
2.4.1 電壓源轉換電路 18
2.4.2 數位/類比轉換電壓準位轉換電路 19
2.5 輸入/輸出板之電路 19
2.5.1 ADC輸入腳位之過電流保護電路 20
2.5.2 過電流保護電路 21
2.5.3 數位/類比轉換電路 23
2.6 外部負載控制電路 23
第三章永磁輔助同步磁阻馬達驅動系統 26
3.1 前言 26
3.2 永磁輔助同步磁阻馬達 28
3.3 永磁輔助同步磁阻馬達數學動態模型與三相座標轉換 30
3.3.1永磁輔助同步磁阻馬達在abc座標系下之數學模型 33
3.3.2永磁輔助同步磁阻馬達在座標系下之數學模型 35
3.3.3永磁輔助同步磁阻馬達在d-q座標系下之數學模型 39
3.3.4永磁輔助同步磁阻馬達反電動勢定義 41
3.4 馬達對位方法 44
3.4.1 同步磁阻馬達對位方法 44
3.4.2 永磁輔助同步磁阻馬達對位方法 47
3.5 增量型編碼器位置迴授和速度估算 49
3.6 電流比例積分控制器之設計 50
3.7 永磁輔助同步磁阻馬達控制架構 52
3.7.1 傳統每安培最大轉矩控制 52
3.7.2 有限元素分析每安培最大轉矩控制 55
3.7.3 利用遞迴式勒壤得模糊類神經網路之智慧型計算轉矩控制 57
第四章永磁輔助同步磁阻馬達之有限元素分析 59
4.1 前言 59
4.2 建立永磁輔助同步磁阻馬達有限元素分析模型 60
4.2.1 Maxwell 2D 模型建立永磁輔助同步磁阻馬達 61
4.2.2 ANSYS功能設定 62
4.3 Simplorer 模擬分析 65
4.3.3 ECE建模設定 66
4.3.4 模擬與實驗結果驗證 68
第五章永磁輔助同步磁阻馬達計算轉矩控制 69
5.1 前言 69
5.2 計算轉矩控制原理 70
5.3 計算轉矩控制穩定性證明 72
第六章利用遞迴式勒壤得模糊類神經網路之智慧型計算轉矩控制 73
6.1 前言 73
6.2 利用遞迴式勒壤得模糊類神經網路之智慧型計算轉矩控制系統 73
6.3 遞迴式勒壤得模糊類神經網路之架構 74
6.4 遞迴式勒壤得模糊類神經網路穩定性證明 78
第七章實驗結果與討論 85
7.1 前言 85
7.2 實驗結果 86
7.3 實驗結果之討論 96
第八章結論與未來展望 98
8.1 結論 98
8.2 未來展望 98
參考文獻 99
作者簡歷 106

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指導教授

林法正(Faa-Jeng Lin)

審核日期

2022-8-24

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