Dissertation/ Thesis

Force Controller Design for Active Suspension by Using Genetic Algorithms and Fuzzy Control

التفاصيل البيبلوغرافية
العنوان: Force Controller Design for Active Suspension by Using Genetic Algorithms and Fuzzy Control
Alternate Title: 應用遺傳演算法與模糊控制於主動懸架系統之力量控制器設計
المؤلفون: Yon-Ji Tsao, 曹永智
Thesis Advisors: Rongshun Chen, Edge Chu Yeh, 陳榮順, 葉莒
سنة النشر: 2002
المجموعة: National Digital Library of Theses and Dissertations in Taiwan
الوصف: 90
Control algorithms are developed for force control in an active vehicle suspension design using genetic algorithms with both quarter car and half car models. The main function of active suspension is to support the vehicle body and isolates the road unevenness to provide ride comfort. Besides, the other important objective is to maintain the contact between tire and road and to minimize the variation of tire deflection for handling control. In this study, force cancellation, virtual damper, skyhook damper, and road-following concepts are proposed to design the force controller for achieving better ride and handling quality. Furthermore, a new approach incorporates the constraints of maximum suspension strokes in the objective function to evaluate the compactness of the suspension working space, as opposed to the traditional integral quadratic form of suspension displacement. Genetic algorithms are employed to obtain a more effective search for optimum control parameters. In addition, a nonlinear model is introduced and a fuzzy control scheme is proposed to deal with the nonlinear tire characteristic, tire deflection limits, and suspension stroke limitations. Computer simulations are performed to verify the proposed control scheme. It is shown both ride comfort and handling quality are greatly improved without exceeding the suspension stroke constraints.
Original Identifier: 090NTHU0311125
نوع الوثيقة: 學位論文 ; thesis
وصف الملف: 94
الاتاحة: http://ndltd.ncl.edu.tw/handle/06530629528957191988
رقم الانضمام: edsndl.TW.090NTHU0311125
قاعدة البيانات: Networked Digital Library of Theses & Dissertations