Control of Four-Wheel-Steering Vehicle Using GA Fuzzv Neural Network
In order to improve the handling and stability of four-wheel-steering (4WS) vehicle, a new 4WS intelligent control system with genetic algorithm (GA) fuzzy neural network (FNN) was put forward. According to the tire cubic formula, a vehicle nonlinear dynamics model was built. Then a vehicle model based on back-propagation (BP) network was identified from the vehicle dynamics. Next a fuzzy neural network controller was designed. Speed, steering angle of front wheel and lateral acceleration were taken as its input variables and steering angle of rear wheel was taken as its output variable. At last GA was used to optimize the fuzzy neural network controller. The results of computer simulation demonstrate that the 4WS intelligent control system with GA fuzzy neural network can markedly reduce the side slip angle and the yaw rate compared with linear 4WS control law and 2WS control law, the entire control system is robust, and the optimization by GA improves the control performance of controller and the design efficiency.
Shijing Wu Enyong Zhu Ming Qin Hui Ren Zhipeng Lei
School of Power and Mechanical Engineering, Wuhan University
国际会议
长沙
英文
869-873
2008-10-20（万方平台首次上网日期，不代表论文的发表时间）