控制理论与应用2025，Vol.42Issue(9)：1746-1756,11.DOI:10.7641/CTA.2024.30579
滚动优化下的对偶启发规划车辆路径跟踪控制
Dual heuristic programming vehicle path tracking control via receding horizon
摘要
Abstract
To improve the path tracking accuracy of intelligent vehicles and reduce the impact of vehicle model un-certainty under high speed and large curvature scenarios,this paper proposes an intelligent vehicle path tracking control strategy based on receding horizon dual heuristic programming(RHDHP).Firstly,a vehicle system model,capable of char-acterizing non linear characteristics of lateral tire forces,is established by combining with the magic formula.Subsequently,an optimal control method using dual heuristic programming(DHP)under the framework of receding horizon optimization is designed.The DHP structure in this method ensures an approximate optimal solution for the vehicle under nonlinear characteristics,while the introduction of receding horizon optimization enhances the adaptability of the vehicle system to environmental changes.Additionally,the convergence of the RHDHP method and the stability of the closed loop system are theoretically analyzed.Finally,the effectiveness of the proposed method is verified through simulations.关键词
车辆路径跟踪/对偶启发式规划/模型预测控制/强化学习Key words
vehicle path tracking/dual heuristic programming/model predictive control/reinforcement learning引用本文复制引用
郭洪艳,李光尧,刘俊,郭景征,谭中秋,吕颖..滚动优化下的对偶启发规划车辆路径跟踪控制[J].控制理论与应用,2025,42(9):1746-1756,11.基金项目
国家自然科学基金项目(62373163,62103162),国家资助博士后研究人员计划项目(GZC20230948)资助.Supported by the National Nature Science Foundation of China(62373163,62103162)and the Postdoctoral Fellowship Program of CPSF(GZC20230948). （62373163,62103162）
