基于MPC和侧偏角软约束的无人驾驶车辆路径跟踪控制  

MPC and Sideslip Angle Soft Constraint Based Path Tracking Control for Selfdriving Vehicles

作　　者：孙博文 张美琪 SUN Bowen;ZHANG Meiqi(School of Automotive Engineering,Yancheng University of Technology,Yancheng 224007,China)

机构地区：[1]盐城工学院汽车工程学院,盐城224007

出　　处：《自动化与仪表》2025年第2期53-56,62,共5页Automation & Instrumentation

摘　　要：为提升无人驾驶汽车路径跟踪控制的精度和稳定性,针对无人驾驶车辆在实现路径跟踪控制功能时的稳定性不足的问题,联合仿真平台通过对车辆4个方向轮侧偏角调整以优化车辆的操纵稳定性。基于侧偏角软约束的算法优化,获得在不同工况下无人驾驶路径跟踪控制算法的优化。MPC路径跟踪横向对比获得不同工况下最优的侧偏角软约束以求对路径跟踪控制算法的优化,该文设计了基于横向位置和前轮航向角预测误差的路径跟踪控制方法。在Carsim-Simulink联合仿真平台上对相关算法进行仿真,结果表明,在加入侧偏角软约束后,10 m/s和20 m/s的路径跟踪控制性能提升明显,稳定性也有较大提升。To improve the accuracy and stability of path tracking control for autonomous vehicles,and to address the issue of insufficient stability in implementing path tracking control functions for autonomous vehicles,the joint simulation platform optimizes the vehicle's handling stability by adjusting the wheel slip angles in all four directions.Algorithm optimization based on soft constraint of sideslip angle to obtain optimization of unmanned driving path tracking control algorithm under different working conditions.MPC path tracking lateral comparison is used to obtain the optimal lateral angle soft constraint under different working conditions in order to optimize the path tracking control algorithm.This paper designs a path tracking control method based on lateral position and front wheel heading angle prediction errors.Simulation of relevant algorithms was conducted on the Carsim-Simulink joint simulation platform,and the results showed that after adding the soft constraint of sideslip angle,the path tracking control performance of10 m/s and 20 m/s was significantly improved,and the stability was also greatly improved.

关 键 词：模型预测控制 侧偏角软约束 路径跟踪控制 软约束控制 

分 类 号：U463.6[机械工程—车辆工程] TP273[交通运输工程—载运工具运用工程]