Comparison Of The Control Strategies Of Four-wheel Steering

Four Wheel Steering(4WS) technologies is one of the effective methods to improve vehicle lateral stability performance. The control strategy of 4WS is designed in this paper. The main content contains:(1) According to momentum theorem and moment of momentum theorem of Newton vector mechanics system, and Newton’s second law, this paper deduce two degrees Four Wheel Steering dynamics model,and with ADAMS/Car establish Four Wheel Steering vehicle multibody dynamics model which includes Car tires, suspension system, steering system, braking system, engine system, body systems and so on.(2) Taking two degrees Four Wheel Steering dynamics model for example, this paper has studied three classic control methods of Four Wheel Steering, through the simulation analysis, the results show that the three control methods in a certain extent improve the manipulation stability of car when low-speed and high-speed steering.(3) Because the two degrees Four Wheel Steering dynamics model is based on numerous hypothesis conditions derived, which is different from actual car in a great extent, so its simulation results has certain limitations. This paper carry out a Four Wheel Steering vehicle co-simulation model based on ADAMS and MATLAB/Simulink. Because the fuzzy control doesn’t require to know the accurate mathematical model of the object, and taking into account that the sideslip angle is not easy to measure during actual vehicle operation, the selection of the yaw rate is selected as the primary control variable.Based on the theory of fuzzy control, the error and error rate between yaw rate of the 4WS vehicle and reference model are proposed as fuzzy controller input and the output is the change of the rear wheel angle. Fuzzy controller and feed-forward controller constitute a controller of rear wheel angle. Through simulating at different vehicle speed and different front wheel input verifying the effectiveness of control strategy.(4) As one of the most common controllers, PID controller does not have a parameter self-tuning function. The paper design a fuzzy PID controller combined with the advantages of fuzzy control. Using yaw rate as the control feedback variable, fuzzy PID controller and feed-forward controller constitute a controller of rear wheel angle. Through simulating at different vehicle speed and different front wheel input verifying the effectiveness of control strategy. Furthermore, analysis and compare the fuzzy control and fuzzy PID control simulation and design process. It concludes that an appropriate controller is selected according to the degree of difficulty to design controller settings and its control effects.