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研究生:許天保
研究生(外文):Tian-bao Syu
論文名稱:風扇板系統之類神經滑模控制器設計
論文名稱(外文):The neuro-sliding mode controller design of fan-plate system
指導教授:江煥鏗
指導教授(外文):Huann-Keng Chiang
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:電機工程系碩士班
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:2009
畢業學年度:97
語文別:中文
論文頁數:78
中文關鍵詞:風扇板滑動模式類神經網路
外文關鍵詞:Fan-plateSliding modeNeural network
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風扇板系統的原理,是利用馬達風扇送出來的風,去吹動薄板,然而風扇板系統具有非線性的特性,傳統上是應用古典控制理論的操作點線性化技巧來設計,此僅適合在操作點附近工作,且易受參數變動或是外在干擾的影響。
本論文首先建立風扇板系統之數學模型,在控制器的部份,針對數學模型推導出風扇板系統的滑動模式控制器,然後根據類神經控制理論,去克服其不確定量,並利用Lyapunov function穩定理論證明設計之控制法則能使系統漸近穩定。最後,經由實驗結果證明上述控制器能有效消除穩態誤差,完成角度控制的目的。
The fan-plate system uses the wind to force and control the angle of plate. However, the system is a nonlinear system. In classical control, the controller is designed by using the operating point linearization method. It is suitable in the small region of operating point and sensitive to the parameter variations and external disturbances.
In this thesis, we first build a model of a fan-plate system. In controller part, the sliding mode controller are proposed. The neural network estimator is designed to overcome parameter variation and external disturbances. The stability of neuro-sliding mode control is approved by Lyapunov stability theory. Finally, we employ the experiments to validate the proposed controller eliminating steady state error and tracking the angle commands.
中文摘要 ----------------------------------------------------------------------------------- i
英文摘要 ----------------------------------------------------------------------------------- ii
誌謝 ----------------------------------------------------------------------------------- iii
目錄 ----------------------------------------------------------------------------------- iv
表目錄 ----------------------------------------------------------------------------------- vi
圖目錄 ----------------------------------------------------------------------------------- vii
符號總表 ----------------------------------------------------------------------------------- x
第一章 緒論----------------------------------------------------------------------------- 1
1.1 風扇系統背景介紹------------------------------------------------------ 1
1.2 研究動機---------------------------------------------------------------------- 1
1.3 文獻回顧---------------------------------------------------------------------- 3
1.4 論文架構---------------------------------------------------------------------- 4
第二章 風扇板系統架構與建模--------------------------------------------- 5
2.1 系統架構---------------------------------------------------------------------- 5
2.2 風扇板系統模型------------------------------------------------------------- 5
第三章 理論探討---------------------------------------------------------------------- 11
3.1 滑動模式控制---------------------------------------------------------------- 11
3.1.1 滑動模式---------------------------------------------------------------------- 11
3.1.2 滑動條件與迫近條件------------------------------------------------------ 13
3.1.3 設計滑動模式控制器之技巧--------------------------------------------- 15
3.2 類神經網路理論------------------------------------------------------------- 18
3.2.1 類神經網路之基本架構--------------------------------------------------- 18
3.2.2 類神經網路的學習方式--------------------------------------------------- 24
3.2.3 輻狀基底函數類神經網路架構------------------------------------------ 25
第四章 類神經滑動模式控制器--------------------------------------------------- 29
4.1 前言----------------------------------------------------------------------------- 29
4.2 傳統滑模控制器設計------------------------------------------------------ 30
4.3 滑動模式控制器建立RBFNN------------------------------------------ 35
第五章 實驗系統---------------------------------------------------------------------- 38
5.1 風扇板系統之整體架構--------------------------------------------------- 38
5.2 風扇板系統之硬體架構--------------------------------------------------- 40
5.3 軟體應用---------------------------------------------------------------------- 44
第六章 模擬結果---------------------------------------------------------------------- 45
6.1 模擬環境---------------------------------------------------------------------- 45
6.2 模擬結果與探討------------------------------------------------------------- 46
第七章 實驗結果---------------------------------------------------------------------- 59
7.1 實驗系統參數---------------------------------------------------------------- 59
7.2 實驗結果探討---------------------------------------------------------------- 61
第八章 結論與未來研究方向------------------------------------------------------ 74
8.1 結論----------------------------------------------------------------------------- 74
8.2 未來研究方向---------------------------------------------------------------- 74
參考文獻 ----------------------------------------------------------------------------------- 75
作者簡介 ----------------------------------------------------------------------------------- 78
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