A Model-Free Control Strategy for Vehicle Lateral Stability With Adaptive Dynamic Programming

This article presents a nonmodel-based controller design for vehicle dynamic systems to improve lateral stability, where output tracking control and adaptive dynamic programming approaches are employed to track the desired yaw rate and, at the same time, mitigate the sideslip angle, roll angle, and roll rate of the vehicle. Moreover, different from some existing optimization methods in control allocation, the proposed control strategies, which distribute tire forces by learning, are only using the information of states, input, and reference signal instead of the knowledge of the vehicle system. The iterative process repeatedly uses the information about state and input to calculate the feedback gain. It can significantly reduce the learning time and computational burden. The effectiveness of the proposed controller design method is shown by CarSim simulations.