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研究生:陳祈銘
論文名稱:主動式懸吊系統之非線性和適應模糊控制
論文名稱(外文):Nonlinear and Adaptive Fuzzy Control for Active Suspension Systems
指導教授:林麗章
學位類別:碩士
校院名稱:國立中興大學
系所名稱:機械工程研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
畢業學年度:87
語文別:中文
論文頁數:126
中文關鍵詞:主動式懸吊系統適應模糊控制
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  主動式懸吊系統若考量致動器動態模式時,本質上為一高度非線性之系統。本文提出懸吊系統之模糊自調式PD控制和適應模糊滑動控制策略,並與Lin和Kanellakopoulos〔11〕之反向步進控制策略進行比較。控制器設計參數之最佳選定,本文更以田口法提出一種離線使用之參數自調法。
  關於模糊自調式PD控制策略之設計,採用類似反向步進控制理論針對串接系統處理方法,將主動式懸吊系統之模式視為由電液伺服致動器次系統和懸吊次系統串接而成。於適應模糊滑動控制策略之設計,則結合了滑動控制、反向步進控制和模糊系統理論,並以李亞譜諾夫理論證明其穩定性。此控制策略以滑動控制策略為主,並引入一適應模糊系統,以李亞譜諾夫方法,推導模糊系統後件部中心值之調適律,以供線上自動調整滑動控制切換部份之增益值。
  電腦模擬結果驗證,反向步進控制策略對於擾動路面之減弱能力不錯,但其反應速率較慢且強健性較其它兩種低;使用適應模糊滑動控制策略,可使懸吊系統得到較快的收斂速率和控制成效,且此控制器在路面有大變動時亦能有效控制,具有較高的強健性。至於模糊自調式PD控制,因所需要計算量較低,控制效果亦不錯,甚具實用性。


  An active suspension system is inherently nonlinear due to the nonlinear electrohydraulic actuatoudynamics. In this thesis, we propose a fuzzy auto-tuning PD control and an adaptive fuzzy sliding mode control for active suspension systems, and compare theri performance with backstepping control proposed by Lin and Kanellakopoulos〔11〕. The Taguchi method is used for the optimal selection of the controller parameters.
  The fuzzy auto-tuning PD controller is composed of a PD control with gains auto-tuned using a fuzzy system and nonlinear controls based on the electrohydraulic actuatou nonlinear model. The design methodology is similar to the backstepping approach based on the cascade structrue of the active suspension systems, however, it is much more simpler. As for the adaptive fuzzy sliding mode control, the traditional sliding mode control, backstepping control and adaptive fuzzy systems desing methodology are integrated, and the Lyapunov theroy is used to construct and analyze the stable adsptive system. The centers of the consequents of an adaptive fuzzy system are on-line adapted to update the gain of the switching part of the sliding control to compensate for the uncertainty.
  Computer simulations show that the ability of the backstepping control to reject the road disturbance is better than the other two strategies, but its respose speed is rather slow, and its robustness is very poor. The suggested adaptive fuzzy sliding mode control can work well and have good robustness, Form implementation point of view, the fuzzy self-tuning PD control is more practical than the other twos since iots control performance is good and the required computation is much lower.

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