使用 區間二型遞迴模糊類神經網路估 測器 之 非線性時變系統 之 智慧型步階回歸控制

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鄧福欣(Fu-Hsin Teng) 查詢紙本館藏

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電機工程學系

論文名稱

使用區間二型遞迴模糊類神經網路估測器之非線性時變系統之智慧型步階回歸控制
(Intelligent Backstepping Control of Nonlinear Time-Varying System with Interval Type-2 Recurrent Fuzzy Neural Network Estimator)

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至系統瀏覽論文 (2029-8-1以後開放)

摘要(中)

本研究提出了一種使用區間二型遞迴模糊神經網路估測器之智慧型步階回歸控制，能夠修正非線性時變系統固有的非線性和時變控制特性。在區間二型遞迴模糊類神經網路估測器之智慧型步階回歸控制中，設計步階回歸控制法則來穩定閉環控制系統，並使用區間二型遞迴模糊神經網路來估計步階回歸設計中的總集不確定項。最初，非線性步階回歸控制的逐步設計被設定用於追蹤週期性參考軌跡，總集不確定項為保守常數。然而，實際應用通常涉及未知且難以預測的總集不確定項，為解決此問題引入區間二型遞迴模糊神經網路來即時估計總集不確定性。應用李亞普諾夫穩定性方法來確保漸近穩定性，從而製定區間二型遞迴模糊神經網路的線上學習演算法。為主動補償區間二型遞迴模糊神經網路的估計誤差亦提出自適應補償器。最後，本研究包括一個案例研究，展示具有最大每安培扭矩控制的同步磁阻馬達位置伺服驅動器的實驗結果。這些結果旨在驗證所提出的區間二型遞迴模糊神經網路智慧型步階回歸控制的有效性和穩健性。

摘要(英)

An intelligent backstepping control with interval type-2 recurrent fuzzy neural network (IBSCIT2RFNN), which is capable of modifying the inherent nonlinear and time-varying control characteristics of a nonlinear time-varying system, is proposed in this research. In the IBSCIT2RFNN, a backstepping control (BSC) law is devised to stabilize the closed-loop control system and the lumped uncertainty in the design of BSC is estimated using an interval type-2 recurrent fuzzy neural network (IT2RFNN). Initially, a step-by-step design of a nonlinear BSC is formulated for tracking periodic reference trajectories, with uncertainties lumped by a conservative constant. However, practical applications often involve unknown and challenging-to-predict lumped uncertainty. To address this, an IT2RFNN is introduced for real-time estimation of the lumped uncertainty. The Lyapunov stability method is applied to ensure asymptotical stability, leading to the formulation of online learning algorithms for the IT2RFNN. In order to proactively compensate the estimation error of the IT2RFNN, an adaptive compensator is also presented. Finally, this research includes a case study presenting experimental results from a synchronous reluctant motor (SRM) position servo drive with maximum torque per ampere (MTPA) control. These results aim to validate the effectiveness and robust qualities of the proposed IBSCIT2RFNN.

關鍵字(中)

★ 步階回歸控制
★ 區間二型遞迴模糊神經網路步階回歸控制、區間二型遞迴模糊
★ 區間二型遞迴模糊神經網路步階回歸控制、區間二型遞迴模糊神經網路
★ 同步磁阻馬達
★ 每安培最大轉矩控制

關鍵字(英)

★ Backstepping control
★ intelligent backstepping control with interval type-2 recurrent fuzzy neural network
★ interval type-2 recurrent fuzzy neural network
★ synchronous reluctant motor
★ maximum torque per ampere

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 7
1.3 論文貢獻 9
1.4 論文大綱 10
2 第二章同步磁阻馬達驅動系統 11
2.1 前言 11
2.2 以DSP為基礎的同步磁阻馬達控制驅動系統 14
2.3 外部負載控制電路 18
2.4 同步磁阻馬達 21
2.5 三相座標轉換以及磁阻轉矩方程式之推導 25
2.6 同步磁阻馬達其對位方式 30
2.7 同步磁阻馬達之比例積分控制器設計 32
2.7.1 電流比例積分控制器之頻域設計 32
2.7.2 速度比例積分控制器之頻域設計 33
2.7.3 位置比例積分控制器之頻域設計 35
3 第三章智慧型步階回歸位置控制 37
3.1 前言 37
3.2 步階回歸控制系統 37
3.3 區間二型遞迴模糊類神經網路之架構 40
3.4 區間二型遞迴模糊類神經網路之穩定性分析 44
3.5 同步磁阻馬達之區間二型遞迴模糊類神經網路估測器之智慧型步階回歸定位控制 51
3.5.1 同步磁阻馬達定位控制 51
3.5.2 同步磁阻馬達之每安培最大轉矩 52
4 第四章同步磁阻馬達有限元素分析與模擬結果 56
4.1 前言 56
4.2 同步磁阻馬達有限元素分析模型 56
4.2.1 Maxwell 2D 模型建立同步磁阻馬達 57
4.2.2 ANSYS功能設定 60
4.2.3 同步磁阻馬達飽和現象 64
4.2.4 電感與電流之變化關係 66
4.3 Simplorer建模和應用 66
4.3.1 ECE簡介與建模設定 67
4.3.2 Simplorer與ECE設定 70
4.3.3 Simplorer與C語言的聯合分析 71
4.4 控制系統於Simplorer分析之模擬結果 74
5 第五章實驗結果與討論 86
5.1 前言 86
5.2 實驗結果 87
5.3 實驗結果討論 97
6 第六章結果與未來展望 98
6.1 結論 98
6.2 未來展望 99
參考文獻 100
作者簡歷 106

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指導教授

林法正(Faa-Jeng Lin)

審核日期

2024-8-7

推文