电气传动2026，Vol.56Issue(6)：76-84,9.DOI:10.19457/j.1001-2095.dqcd26531
基于扩展卡尔曼滤波器的MPC车辆轨迹跟踪控制
MPC Vehicle Trajectory Tracking Control Based on Extended Kalman Filter
摘要
Abstract
To enhance the trajectory tracking control stability of driverless vehicles under real-world noise interference,a vehicle trajectory tracking controller based on model predictive control(MPC)integrated with the extended Kalman filter algorithm(EKF-MPC)was constructed.Firstly,a vehicle dynamics model was established,and the trajectory tracking controller,objective function,relevant constraint conditions were designed to address nonlinear vehicle characteristics and measurement noise.The MPC algorithm was applied to solve for the optimal control inputs at each sampling instant.Meanwhile,the extended Kalman state estimator dynamically updated its gain matrices to calculate the posterior state matrix,effectively counteracting the adverse effects of vehicle nonlinearity and state measurement noise.Joint simulation verification was conducted using Matlab and CarSim,and the results show that compared with the conventional MPC controller,the EKF-MPC controller improves safety by 2.3%and feasibility by 37.7%across different road sections.Its stability is significantly enhanced,these findings provide strong support for the development of vehicle trajectory tracking control technology.关键词
轨迹跟踪/扩展卡尔曼滤波/模型预测控制/CarSim软件Key words
trajectory tracking/extended Kalman filter(EKF)/model predictive control(MPC)/CarSim software分类
交通工程引用本文复制引用
霍婷婷,贾志龙,晏永,张庆..基于扩展卡尔曼滤波器的MPC车辆轨迹跟踪控制[J].电气传动,2026,56(6):76-84,9.基金项目
2024年宁夏回族自治区自然科学基金(2024AAC03317) （2024AAC03317）
