Nonlinear Design Approach to Four-Wheel-Steering Systems Using Neural Networks

Four-wheel-steering (4WS) systems have been studied and developed with remarkable success from the viewpoint of vehicle dynamics. Most of the control methods require a linearized bicycle model of the actual vehicle system which is however strongly influenced by tire nonlinearity. This paper proposes a new method to design the 4WS system taking into account the nonlinear characteristics of tires and suspensions. For this purpose integration of artificial neural network and linear control theory is introduced for the identification and control of a nonlinear vehicle model structured using a software for multi-body dynamic analysis (ADAMS). This model takes into account the nonlinear characteristics of actual vehicles with tires modeled by “magic formula”. The results of computer simulations show that the proposed nonlinear approach is efficient in improving the handling and stability of vehicles.