主办:陕西省汽车工程学会
ISSN 1671-7988  CN 61-1394/TH
创刊:1976年

Automobile Applied Technology ›› 2026, Vol. 51 ›› Issue (17): 46-51.DOI: 10.16638/j.cnki.1671-7988.2026.017.007

• Intelligent Connected Vehicle • Previous Articles    

Research on trajectory tracking control based on the MPC algorithm

YUAN Liqiu, DUAN Xinyue   

  1. School of New Energy Vehicles, Sichuan Vocational College of Science and Technology
  • Published:2026-09-07
  • Contact: YUAN Liqiu

基于 MPC 算法轨迹跟踪控制研究

袁丽秋,段新月   

  1. 四川科技职业学院 新能源汽车学院
  • 通讯作者: 袁丽秋
  • 作者简介:袁丽秋(1999-),女,硕士,讲师,研究方向为汽车动力学控制

Abstract: Aiming at the lane-changing trajectory tracking control problem of intelligent vehicles, this paper proposes a trajectory tracking control strategy based on model predictive control (MPC). Firstly, a 2-degree-of-freedom vehicle dynamic model is established, and the state-space expression is adopted to describe the lateral motion characteristics of the vehicle. Secondly, a fifth-order polynomial lane-changing trajectory is designed as the desired path, which features continuous and smooth curvature and heading angle. Then, a trajectory tracking controller is designed based on the MPC algorithm, and the 2-degree-of-freedom vehicle model is discretized. Taking the lateral position deviation and heading angle deviation as state variables and the front-wheel steering angle as the control variable, a cost function containing tracking error and control increment is constructed.Constraint conditions including front-wheel steering angle, steering-angle change rate and lateral acceleration are introduced, and the optimal control problem is transformed into a quadratic programming problem for solution. Finally, the co-simulation of MATLAB/Simulink and CarSim is used to verify the feasibility and effectiveness of the proposed control strategy. Simulation results show that the designed controller achieves favorable tracking performance and high tracking accuracy under different vehicle-speed working conditions. The maximum lateral displacement error is kept within 0.045 m, and the front-wheel steering angle varies smoothly.

Key words: model predictive control; trajectory tracking; lane changing control; two-degree-offreedom vehicle model; co-simulation

摘要: 针对智能汽车换道轨迹跟踪控制问题,文章提出了一种基于模型预测控制(MPC)的 轨迹跟踪控制策略。首先,建立了车辆二自由度动力学模型,采用状态空间表达式描述车辆 横向运动特性;其次,设计了五次多项式换道轨迹作为期望路径,该轨迹具有曲率和航向角 连续平滑的特性;然后,基于 MPC 算法设计了轨迹跟踪控制器,并离散化处理了二自由度车 辆模型,以横向位置偏差和航向角偏差为状态量,以前轮转角为控制量,构建了包含跟踪误 差和控制增量的代价函数,并引入前轮转角、转角变化率及侧向加速度等约束条件,将最优 控制问题转化为二次规划问题进行求解;最后,采用 MATLAB/Simulink 与 CarSim 联合仿真, 对该控制策略可行性与有效性进行了验证。仿真结果表明,所设计控制器在不同车速工况下 均具有良好的跟踪性能,跟踪精度高,最大横向位移误差控制在 0.045 m 以内,前轮转角变 化平稳

关键词: 模型预测控制;轨迹跟踪;换道控制;二自由度车辆模型;联合仿真