An individualized robust stability control strategy for active front steering vehicles

To improve the vehicle stability and driver steering performance, this paper presents an individualized yaw stability control strategy based on H infinity robust control for active front steering (AFS) vehicles. A driver-vehicle system, including a driver steering model and a vehicle dynamics model with AFS, is formed. To analyze the steering characteristics of different drivers, a set of driving data of 36 drivers is collected, and the driver's characteristics parameters are identified by using the particle swarm optimization (PSO) algorithm. A general evaluation function considering the trajectory tracking performance, vehicle stability, driver workloads, and driver's characteristics parameters are established to evaluate the comprehensive steering performance. To accomplish the personalized control of vehicle yaw stability, an individualized H infinity robust yaw stability controller is presented by adjusting the gain of the weighting function according to the general evaluation of each driver. Driver-in-the-loop experiment is conducted based on the Matlab/Simulink-CarSim (R)-Prescan co-simulation platform, and the results demonstrates that the proposed control strategy can provide driver with individualized driving assistance while improving the overall driving performance and reducing the driver's workloads.