A fuzzy synthesis control strategy for active four-wheel steering based on multi-body models

Active steering systems can help the driver to master critical driving situations. This paper presents a fuzzy logic control strategy on active steering vehicle based on a multi-body vehicle dynamic model. The multi-body vehicle dynamic model using ADAMS can accurately predict the dynamic performance of the vehicle. A new hybrid steering scheme including both active front steering (applying an additional front steering angle besides the driver input) and rear steering is presented to control both yaw velocity and sideslip angle. A set of fuzzy logic rules is designed for the active steering controller, and the fuzzy controller can adjust both sideslip angle and yaw velocity through the co-simulation between ADAMS and the Matlab fuzzy control unit with the optimized membership function. To ensure the design of high-quality fuzzy control rules, a rule optimization strategy is introduced. The fuzzy control parameters are optimized and analyzed by a combined optimization algorithm (the Simulated Annealing method (SA) and the Nonlinear Programming Quadratic Line search (NLPQL) method) combined with the response surface model (RSM). A single-lane-change experiment is used to validate the effectiveness of the active steering system. Simulation results show that active steering with the fuzzy control logic strategy can improve vehicle handling stability greatly compared to a four-wheel steering controller and traditional front-wheel steering.