Steering control system design and simulation for intelligent vehicle
To suppress the robustness of the control system due to the variation of vehicle internal parameters and external disturbances in the path tracking process of intelligent vehicles, this paper proposes a recursive sliding mode control method.Based on a two-degree-of-freedom vehicle dynamics model, a recursive sliding mode controller is designed by introducing the lateral error between the vehicle and the desired position to build a recursive sliding mode surface.Considering the requirement of system uncertainty on the robustness of the control system, an estimator based on radial basis function neural network is designed for the compensation in the feedback loop.Compared with the existing control methods, the proposed one quickly tracks the desired path without overshoot and effectively overcomes the external disturbance.It improves the vehicle's performance index by 86.65％ on the serpentine path tracking and by 81.35％ on the continuous lane change path tracking, greatly improving the robustness and anti-interference of the system.Our results show this method improves the dynamic response performance of path tracking of unmanned vehicles, meets the requirements of stable tracking of desired paths, and thus has huge application potentials.
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