重庆理工大学学报2024，Vol.38Issue(3)：99-108,10.DOI:10.3969/j.issn.1674-8425(z).2024.02.010
自适应预测时域参数MPC车辆轨迹跟踪控制
MPC vehicle trajectory tracking control with adaptive predictive horizon parameters
摘要
Abstract
To improve the accuracy and stability of trajectory tracking control of unmanned vehicles at different speeds,the traditional fixed prediction horizon Model Predictive Control(MPC)controller is optimized and a vehicle trajectory tracking control strategy based on adaptive prediction horizon parameter MPC is proposed in this paper.The grey relational method is employed to determine the optimal horizon parameters of MPC under different target speed conditions.The Fourier approximation method is employed to fit the prediction horizon parameters,and the semi-empirical model predicting the horizon parameters with the change of vehicle speed is obtained by combining the vehicle dynamics model and MPC algorithm.The model selects the relative optimal prediction horizon according to the change of the target speed of the vehicle trajectory tracking.Our simulation comparison test and real vehicle test show the adaptive prediction horizon parameter MPC controller reduces the trajectory tracking error and improves the solution speed.The mean yaw angle deviation is reduced by 14.7%and the mean lateral deviation is down by 21.7%.Meanwhile,it is highly adaptable to different vehicle speeds.关键词
参数自适应/模型预测控制/轨迹跟踪/车辆控制Key words
parameter adaptation/model predictive control/trajectory tracking/vehicle control分类
交通工程引用本文复制引用
吴长水,高绍元..自适应预测时域参数MPC车辆轨迹跟踪控制[J].重庆理工大学学报,2024,38(3):99-108,10.基金项目
国家自然科学基金项目(51609132) （51609132）
