Intelligent Vehicle Path Tracking Control Based on Moving Horizon Sliding Mode Control

Abstract

Due to the strong nonlinearity and the uncertainty of the vehicle, accurate path tracking control becomes a challenge. This paper proposes a path tracking control strategy that can simultaneously consider the dynamic characteristics of tracking performance and system constraints. The control strategy is based on moving horizon sliding mode control (MHSMC), in which the sliding mode surface is used to construct the prediction model, and the effects of parameter perturbation and external disturbance are eliminated through feedback correction and rolling optimization, then the prediction results of the model output are corrected so as to make sure optimal performance control under system constraints. The MHSMC combines the advantages of sliding mode control and moving horizon control, effectively improving the dynamic performance and robustness of the system. The simulation results of typical conditions show that the control strategy proposed in this paper can make the vehicle track the reference path well and has strong robustness.