Due to the complicated driving conditions, the influence of the external disturbance and the system uncertainty, the traditional active front-steering control methods which are based on the exact mathematical model cannot meet the control requirements. This article presents a new active front-steering control strategy which is based on active disturbance rejection control for vehicle yaw stability control. The proposed controller can dynamically estimate and compensate the total disturbance, which enables it to provide good control performance in a range of conditions without the need for a sophisticated vehicle model. In this article, the implementation of the active disturbance rejection control–based yaw stability controller is introduced in detail, and the convergence of the extended state observer and the stability of the whole controller are theoretically proved. In order to verify the effectiveness of the proposed control strategy, a co-simulation environment is used to carry out real-time simulations on typical driving conditions to verify the performances of the proposed controller. The simulation results show that the proposed controller can effectively improve the yaw stability of the vehicle and has strong robustness.
Integrated bees algorithm and artificial neural network to propose an efficient controller for active front steering control of vehicles
