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系統識別號 U0002-1507201422393700
中文論文名稱 適應性模糊類神經網路控制器設計與實現
英文論文名稱 Design and Implementation of an Adaptive Fuzzy Neural Network System
校院名稱 淡江大學
系所名稱(中) 電機工程學系碩士班
系所名稱(英) Department of Electrical Engineering
學年度 102
學期 2
出版年 103
研究生中文姓名 張峻瑋
研究生英文姓名 Chun-Wei Chang
學號 601460214
學位類別 碩士
語文別 中文
口試日期 2014-07-04
論文頁數 71頁
口試委員 指導教授-許駿飛
委員-葉明豐
委員-李世安
中文關鍵字 模糊類神經網路  滑動模式控制  智慧型控制 
英文關鍵字 fuzzy neural network  sliding-mode control  intelligent control 
學科別分類 學科別應用科學電機及電子
中文摘要 近十年來,模糊類神經網路控制器已成功應用至各種不同的控制問題上。但是,模糊類神經網路只使用明確的歸屬度而無法包含語言不確定性,且使用前饋式網路架構只能具有靜態的響應。為了克服其缺點,本論文提出具有擾動項模糊類神經網路及具有迴授項模糊類神經網路兩種網路架構。藉由調整擾動項的振幅與頻率來克服人們對數值描述感覺的不確定性,以及利用回授項捕捉動態響應及訊息儲存的能力。並進一步,本論文提出適應性模糊類神經滑動模式控制器與適應性模糊類神經二階滑動模式控制器,運用上述所介紹的兩種新型模糊類神經網路架構來線上學習系統動態方程式。同時,本論文設計了一個平滑補償器來克服模糊類神經網路的學習近似誤差所造成的影響。最後,利用混沌動態系統及倒單擺擺動系統來測試所提出的控制方法,經由模擬結果驗證其可以獲得良好的控制結果。
英文摘要 In recent years, fuzzy neural network (FNN) has been developed. But the FNN have two major drawbacks, one is their application domain is limited to the static problem due to their feedforward network structure, and the other is their unable to directly handle the rule uncertainties due to the membership function is a crisp number. To attack this problem, this paper proposes a perturbed fuzzy neural network (PFNN) and recurrent fuzzy neural network (RFNN). Meanwhile, a fuzzy neural network sliding-mode control (FNSMC) system and a fuzzy neural network second-order sliding-mode control (FNSSMC) system are proposed. Since the RFNN has an internal feedback loop, it can capture the dynamic response with an external feedback. On the other hand, the PFNN uses a perturbed membership function to handle the information uncertainties when it is hard to exactly determine the grade of the value of a basis function. To cope with the approximator error, a smooth compensator is proposed to reduce chattering in the control input. Finally, a chaotic system and an inverted pendulum are applied to example studies. The simulation results show that the proposed two control methods can achieve favorable control performance.
論文目次 目錄
中文摘要....................................................I
英文摘要...................................................II
目錄.....................................................III
表目錄......................................................V
圖目錄.....................................................VI
第一章 緒論.................................................1
1.1 研究動機與目的 ..........................................1
1.2 文獻回顧................................................4
1.3 論文大綱................................................6
第二章 新型模糊類神經網路介紹...................................8
2.1 模糊類神經網路...........................................8
2.2 具擾動項模糊類神經網路....................................11
2.3 具回授項模糊類神經網路....................................20
第三章 適應性模糊類神經滑動模式控制設計..........................27
3.1 簡介..................................................27
3.2 滑動模式控制器設計.......................................28
3.3 傳統適應性模糊類神經滑動模式控制器設計.......................30
3.4 新型適應性模糊類神經滑動模式控制器設計.......................34
3.5 模擬結果...............................................37
第四章 適應性模糊類神經二階滑動模式控制設計......................46
4.1 簡介..................................................46
4.2 二階滑動模式控制器設計....................................47
4.3 傳統適應性模糊類神經二階滑動模式控制設計.....................50
4.4 新型適應性模糊類神經二階滑動模式控制設計.....................54
4.5 模擬結果...............................................58
第五章 結論與未來的研究發展...................................67
5.1 結論..................................................67
5.2 未來方向...............................................68
參考文獻...................................................69

表目錄
表3.1 適應性模糊類神經滑動模式控制器之狀態x控制響應之誤差比較表.....45
表3.2 適應性模糊類神經滑動模式控制器之狀態x'控制響應之誤差比較表....45
表3.3 適應性模糊類神經滑動模式控制器之具回授項模糊類神經近似器輸出z^之誤差比較表...................................................45
表4.1 適應性模糊類神經二階滑動模式控制器之狀態x控制響應之誤差比較表..66
表4.2 適應性模糊類神經二階滑動模式控制器之狀態x'控制響應之誤差比較表.66
表4.3 適應性模糊類神經二階滑動模式控制器之具回授項模糊類神經近似器輸出 z^之誤差比較表..............................................66

圖目錄
圖2.1 模糊類神經網路架構......................................9
圖2.2 (a)傳統模糊集合(b)第二型模糊集合......................12
圖2.3 第二型高斯模糊集合.....................................12
圖2.4 具擾動項模糊類神經網路..................................14
圖2.5 不同參數下的具擾動項高斯歸屬函數..........................16
圖2.6 回授式類神經網路架構....................................21
圖2.7 具回授項模糊類神經網路..................................22
圖3.1 傳統適應性模糊類神經滑動模式控制系統方塊圖..................30
圖3.2 新型適應性模糊類神經滑動模式控制系統方塊圖..................34
圖3.3 倒單擺模擬圖..........................................37
圖3.4 較小負載狀態下傳統適應性模糊類神經滑動模式控制模擬結果........41
圖3.5 較大負載狀態下傳統適應性模糊類神經滑動模式控制模擬結果........42
圖3.6 較小負載狀態下新型適應性模糊類神經滑動模式控制模擬結果........43
圖3.7 較大負載狀態下新型適應性模糊類神經滑動模式控制模擬結果........44
圖4.1 傳統適應性模糊類神經二階滑動模式控制系統方塊圖...............50
圖4.2 新型適應性模糊類神經二階滑動模式控制系統方塊圖...............54
圖4.3 不受控制的混沌動力系統行為...............................59
圖4.4 狀況一下之傳統適應性模糊類神經二階滑動模式控制結果...........62
圖4.5 狀況二下之傳統適應性模糊類神經二階滑動模式控制結果...........63
圖4.6 狀況一下之新型適應性模糊類神經二階滑動模式控制結果...........64
圖4.7 狀況二下之新型適應性模糊類神經二階滑動模式控制結果...........65
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