Two-Level LPV Model Based Sliding Mode Predictive Control with Actuator Input Delay for Vehicle Yaw Stability

For the improvement of the vehicle yaw stability, this paper studies the control problem of the active front steering (AFS) system with actuator input delay. A novel sliding mode predictive control method to handle actuator input delay is proposed for the AFS system. Firstly, considering the nonlinearities of the vehicle system, a linear parameter varying vehicle system model with two-level structure is proposed to capture the vehicle dynamic behaviors. Secondly, to deal with the issues of actuator input delay and system constraints, a novel sliding mode predictive control method is put forward. In the process of controller design, a sliding mode control algorithm is employed for the improvement of the robustness of the control system, and then a model predictive control algorithm is employed to deal with system constraints. Thirdly, for the improvement of the feasibility of the proposed controller in the actual system, the objective function of the sliding mode predictive control strategy is optimized by using the particle swarm optimization algorithm. Finally, the joint simulations of Carsim and Matlab/Simulink are conducted to validate the performance of the controller. The experimental results show that the proposed control method is effective to improve the vehicle yaw stability.