A fuzzy control strategy and optimization for four wheel steering system

Jie Zhang, Yunqing Zhang, Liping Chen, Jingzhou Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

This paper presents a fuzzy logic control strategy on four-wheel steering(4WS) vehicle based on a multi-body vehicle dynamic model. The multi-body vehicle dynamic model based on ADAMS can accurately predict the dynamics performance of the vehicle. Fuzzy logic is applied to track the yaw velocity of the two degrees of freedom ideal model through the co-simulation of ADAMS and Matlab Fuzzy control unit with the optimized membership function. The fuzzy control parameters are optimized and analyzed by a combined optimization algorithm (Genetic Algorithm (GA) and Nonlinear Programming Quadratic Line search (NLPQL) method) combined with response surface model (RSM). Single lane change test is chosen to validate the fuzzy control logic strategy. Simulation result shows that four-wheel steering vehicle with the fuzzy control logic strategy can improve vehicle handling stability greatly comparing with traditional front wheel steering.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Vehicular Electronics and Safety, ICVES
DOIs
StatePublished - 2007
Event2007 IEEE International Conference on Vehicular Electronics and Safety, ICVES - Beijing, China
Duration: Dec 13 2007Dec 15 2007

Publication series

Name2007 IEEE International Conference on Vehicular Electronics and Safety, ICVES

Conference

Conference2007 IEEE International Conference on Vehicular Electronics and Safety, ICVES
Country/TerritoryChina
CityBeijing
Period12/13/0712/15/07

Keywords

  • Four-wheel steering
  • Fuzzy control
  • Genetic algorithm
  • Multi-body

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