Trajectory tracking control of autonomous vehicles based on event‐triggered model predictive control

作者：Jindou Zhang, Zhiwen Wang, Long Li, Kangkang Yang, Yanrong Lu · 发表于：IET Intelligent Transport Systems · 年份：2024 · DOI：10.1049/itr2.12589 · 被引用次数：8 · 研究领域：Vehicle Dynamics and Control Systems、Electric and Hybrid Vehicle Technologies、Real-time simulation and control systems

Abstract This paper presents a lateral control scheme based on event‐triggered model predictive control for trajectory tracking of autonomous vehicles. Firstly, the augmentation system is constructed based on the known road curvature information, and the model predictive controller is utilized to obtain the optimal control sequence. Then, an event‐triggered mechanism is introduced to improve the real‐time performance of the control system. The strategy targets to reduce the computational complexity and solving frequency of the optimization problem. In addition, a contraction constraint is structured using the backstepping control strategy to ensure the stability of the control system. Finally, experiments are conducted through the CarSim/Simulink joint simulation platform, and compared with the traditional model predictive control, the method proposed in this paper has better tracking accuracy and improves the real‐time performance of the control system.