Abstract：Aimed at keeping side slip angle at zero while inputting small steering angle, and keeping front axle anti-slip while inputting large steering angle, a control strategy for four-wheel steering （4WS） vehicle was proposed. Three degrees of freedom 4WS vehicle dynamic model including nonlinear characteristic of tyres and roll motion was established with Simulink. The neural network controller of 4WS vehicle was constructed based on double hidden layers BP neural network. Simulation results show that the neural network controller keeps front axle from side slip and maintains side slip angle at zero in most cases, and the control errors are less than those in the proportional angle control and the yaw rate feedback control. In addition, the amplitude of yaw rate is similar to that of front-wheel-steering vehicle and the steady response of lateral acceleration and the body roll angle are decreased than front wheel steering vehicle.
林棻, 赵又群, 姜宏. 基于Simulink的四轮转向汽车神经网络控制策略仿真[J]. 江苏大学学报（自然科学版）, 2008, 29(5): 390-393.
Lin Fen, Zhao-Youqun, Jiang-Hong. Simulation of neural network control strategy for four-wheel-steering vehicle based on Simulink[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2008, 29(5): 390-393.
2008, Vol. 29 
