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研究生:張志袁
研究生(外文):Chih-Yuan Chang
論文名稱:主動式懸吊系統之自組織模糊滑動徑向基類神經網路控制器的設計
論文名稱(外文):Design of a Self-Organizing Fuzzy Sliding-Mode Radial Basis-Function Neural-Network Controller for ActiveSuspension Systems
指導教授:林震林震引用關係
口試委員:陳雙源連瑞敬
口試日期:2012-07-25
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:機電整合研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:97
中文關鍵詞:主動式懸吊系統模糊控制自組織滑動模式徑向基底函數類神經網路
外文關鍵詞:Active suspension systemfuzzy controlself-organizingsliding moderadial basis-function neural network
相關次數:
  • 被引用被引用:0
  • 點閱點閱:125
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  • 下載下載:20
  • 收藏至我的研究室書目清單書目收藏:1
主動式懸吊系統一般都具有複雜和非線性的特點,使得該系統的數學模型難以被正確地建立或估測出來,所以很難設計出以模式為基礎的控制器。為了解決問題,本研究發展出自組織模糊滑動徑向基類神經網路控制器(SFSRBNC) 來操控主動式懸吊系統, 以評估其控制性能。該SFSRBNC 解決了自組織模糊控制器(SOFC) 和自組織模糊滑動模式控制器(SFSC) 在參數上選擇的問題。而且該SFSRBNC 也解決了自組織模糊徑向基類神經網路控制器(SFRBNC) 穩定性的問題。經由模擬結果證實, SFSRBNC 比SOFC, SFSC,SFRBNC 以及被動式控制能提供更好的控制性能, 並且也能提高懸吊系統的使用壽命, 乘坐汽車的舒適性以及汽車的操控性。

Active suspension systems generally have complicated and nonlinear characteristics,so it is difficult to design a model-based controller for the control of such systems.
To overcome the difficulty, this study developed a self-organizing fuzzy sliding-mode radial
basis-function neural-network controller (SFSRBNC) to manipulate an active suspension system and then evaluate its control performance. The SFSRBNC not only eliminates
the problem caused by the inappropriate selection of parameters in both a self-organizing fuzzy controller (SOFC) and a self-organizing fuzzy sliding-mode controller (SFSC), but also solves the stability problem of a self-organizing fuzzy radial basis-function neuralnetwork
controller (SFRBNC) application. Simulation results demonstrated that the SFSRBNC achieved better control performance than the SOFC, SFSC, SFRBNC as well as
passive control, in terms of the ride comfort and the road-holding capability of the vehicle,as well as the service life of the suspension system.

中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . .i
英文摘要. . . . . . . . . . . . . . . . . . . . . . . . . ii
誌謝 . . . . . . . . . . . . . . . . . . . . . . . . . . iii
目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . iv
圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . vi
第一章緒論 . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究動機與目的 . . . . . . . . . . . . . . . . . . . . 1
1.2 懸吊系統分類 . . . . . . . . . . . . . . . . . . . . . 1
1.3 文獻回顧 . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 本文架構 . . . . . . . . . . . . . . . . . . . . . . . 6
第二章系統的數學模式 . . . . . . . . . . . . . . . . . . . 7
2.1 主動式懸吊系統簡介 . . . . . . . . . . . . . . . . . .7
2.2 主動式懸吊系統之數學模式. . . . . . . . . . . . . . . .8
第三章控制器的設計. . . . . . . . . . . . . . . . . . . . 11
3.1 模糊控制理論. . . . . . . . . . . . . . . . . . . . . 11
3.2 自組織模糊控制器的設計. . . . . . . . . . . . . . . . 15
3.2.1 自組織模糊演算法 . . . . . . . . . . . . . . . . . .15
3.2.2 主動式懸吊系統之自組織模糊控制器的設計 . . . . . . .18
3.3 自組織模糊滑動模式控制器的設計. . . . . . . . . . . . 19
3.3.1 滑動模式控制理論 . . . . . . . . . . . . . . . . . .19
3.3.2 主動式懸吊系統之自組織模糊滑動模式控制器的設計. . . 22
3.4 自組織模糊徑向基類神經網路控制器的設計. . . . . . . . 23
3.4.1 徑向基底函數類神經網路. . . . . . . . . . . . . . . 23
3.4.2 主動式懸吊系統之自組織模糊徑向基類神經網路控制器
的設計. . . . . . . . . . . . . . . . . . . . . . . 27
3.5 主動式懸吊系統之自組織模糊滑動徑向基類神經網路控制
器的設計. . . . . . . . . . . . . . . . . . . . . . . 28
第四章數值模擬結果與分析. . . . . . . . . . . . . . . . . 29
4.1 正弦波路面擾動之懸吊系統的主動控制. . . . . . . . . . 31
4.2 凸塊路面擾動之懸吊系統的主動控制. . . . . . . . . . . 51
4.3 隨機路面擾動之懸吊系統的主動控制. . . . . . . . . . . 71
第五章結論. . . . . . . . . . . . . . . . . . . . . . . . 91
5.1 本文重要結論. . . . . . . . . . . . . . . . . . . . . 91
5.2 未來展望. . . . . . . . . . . . . . . . . . . . . . . 92
參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . 93
著作發表. . . . . . . . . . . . . . . . . . . . . . . . . 97

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