Research on Vehicle Four-Wheel Steering Based on Model-Free Adaptive Control

For the issue that it is difficult to build an accurate mathematical model for a strongly coupled and nonlinear four-wheel steering vehicle, a model-free adaptive control scheme is proposed in this thesis. The method of compact form dynamic linearization is used to transform the nonlinear vehicle model into a discrete dynamic linearization data model. The controller is designed by using the sideslip angle and yaw rate of vehicles, and the immune algorithm is adopted to optimize the relevant parameters. To simulate the control system, CarSim and MATLAB/Simulink were introduced into my research. The results showed that the model-free adaptive control strategy can improve the vehicle's handling stability more significantly, compared with the model-based proportional control four-wheel steering strategy, which verified the feasibility and effectiveness of the designed model-free adaptive control scheme.