基於智慧型積分滑模控制之內藏式永磁同步馬達驅動強健無差拍預測電流控制

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姓名

徐義茗(I-Ming Hsu) 查詢紙本館藏

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電機工程學系

論文名稱

基於智慧型積分滑模控制之內藏式永磁同步馬達驅動強健無差拍預測電流控制
(Robust Deadbeat Predict Current Control Using Intelligent Integral Sliding Mode Control for Interior Permanent Magnet Synchronous Motor Drive)

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至系統瀏覽論文 (2029-8-1以後開放)

摘要(中)

本文提出了一種針對內藏式永磁同步馬達電機驅動的強健無差拍電流控制，該方式建立在智慧型積分滑模控制基礎上，並結合自適應類神經網路。無差拍電流控制以其對電機驅動參數變化和外部干擾的敏感性而聞名，因此對其進行增加強健性的需求日益迫切。為了解決這個問題，本研究旨在減輕無差拍電流控制的參數敏感性，同時增強對干擾的整體強健性。首先推導考慮內藏式永磁同步馬達 dq軸時間延遲影響的無差拍電流控制建模和控制策略，還計算了dq軸的干擾項。提供積分滑模控制的詳細分析，該分析可以應對內藏式永磁同步馬達驅動的dq軸電流控制中的模型參數不匹配和干擾。此外為減小積分滑模控制的開關增益，提出使用自適應神經網路來估計dq軸干擾項的方法，從而實現智慧型積分滑模控制。實驗所使用之硬體為應用德州儀器公司生產之浮點數數位訊號處理器TMS320F28075之內藏式永磁同步馬達伺服驅動系統。

摘要(英)

This study introduces a robust deadbeat predict current control (DPCC) scheme designed for an interior permanent magnet synchronous motor (IPMSM) drive. The scheme is built upon an intelligent integral sliding mode control (ISMC) by using an adaptive neural network (ANN). The DPCC, known for its sensitivity to motor drive parameter variations and external disturbances, prompted the need for enhanced robustness in current control. To address this, the proposed approach aims to mitigate the parameter sensitivity of DPCC and enhance the overall robustness of current control against disturbances. In this study, first, the modeling and control strategies of DPCC considering the effect of time delay for the dq-axis of IPMSM are derived. The disturbance terms of dq-axis are also formulated. Then, the detailed analyses of ISMC which can confront the model parameter mismatch and disturbances for the dq-axis current control of the IPMSM drive are provided. In addition, in order to reduce the switch gains of the ISMC, an ANN is proposed to estimate the disturbance terms of dq-axis resulted in an intelligent ISMC. Additionally, some experimental results are demonstrated to verify the effectiveness of the proposed robust DPCC using intelligent ISMC for the IPMSM drive in the constant toque region.

關鍵字(中)

★ 自適應神經網路
★ 無差拍電流控制
★ 內藏式永磁同步馬達
★ 積分滑模控制

關鍵字(英)

★ Adaptive neural network
★ deadbeat predict current control
★ interior permanent magnet synchronous motor
★ integral sliding mode control

論文目次

摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目綠 vii
表目錄 xiii
1 第一章緒論 1
1.1 研究動機 1
1.2 文獻回顧與簡介 2
1.3 論文貢獻 4
1.4 論文大綱 4
2 第二章內藏式永磁同步馬達變頻驅動器硬體介紹 5
2.1 簡介 5
2.2 變頻器 5
2.3 磁粉式煞車 6
2.4 數位訊號處理器 7
2.5 驅動控制電路板 10
3 第三章內藏式永磁同步馬達驅動系統 15
3.1 前言 15
3.2 三相座標轉換 16
3.3 內藏式永磁同步馬達在abc座標系下之數學模型 19
3.4 內藏式永磁同步馬達在αβ座標系下之數學模型 21
3.5 內藏式永磁同步馬達在d-q座標系下之數學模型 25
3.6 凸極式反電動勢定義 27
3.7內藏式永磁同步馬達控制系統 29
3.7.1 傳統PI速度控制與電流控制 30
3.7.2 速度比例積分控制器設計 33
3.7.4 每安培最大轉矩控制 34
3.7.5 積分滑模控制之無差拍預測電流控制、智慧型積分滑模控制之無差拍預測電流控制 35
4 第四章基於積分滑模控制之無差拍預測電流控制 37
4.1 前言 37
4.2 無差拍預測電流控制 38
4.3 參數誤差與外部擾動估計 40
4.4 基於積分滑模控制之無差拍預測電流控制 41
4.5 基於積分滑模控制之無差拍預測電流控制穩定性證明 42
5 第五章基於自適應神經網路的智慧型積分滑模控制 43
5.1 前言 43
5.2 基於自適應類神經網路的智慧型積分滑模控制 43
5.3 自適應類神經網路 44
5.4 線上學習法則 45
5.5 網路收斂性 46
6 第六章模擬與實驗結果 48
6.1 前言 48
6.2 模擬結果 50
6.3 模擬結果分析與討論 61
6.4 實驗結果 63
6.5 實驗結果分析與討論 70
6.6 頻寬量測與比較 72
7 第七章結論與未來研究方向 84
7.1 結論 84
7.2 未來展望 84
參考文獻 86
作者簡歷 91

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指導教授

林法正(Faa-Jeng Lin)

審核日期

2024-8-7

推文