汽车工程 ›› 2021, Vol. 43 ›› Issue (8): 1187-1194.doi: 10.19562/j.chinasae.qcgc.2021.08.009

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基于动力学模型预测控制的铰接车辆多点预瞄路径跟踪方法

李斯旭,徐彪,胡满江(),边有钢,陈晓龙,孙宁   

  1. 湖南大学机械与运载工程学院,汽车车身先进设计制造国家重点实验室,长沙 410082
  • 收稿日期:2021-02-24 修回日期:2021-04-23 出版日期:2021-08-25 发布日期:2021-08-20
  • 通讯作者: 胡满江 E-mail:manjiang_h@hnu.edu.cn
  • 基金资助:
    湖南省重点领域研发计划(2019GK2151);国家自然科学基金(52002126);汽车车身先进设计制造国家重点实验室(61775006)

A Dynamic Model Predictive Control Approach for Multipoint Preview Path Tracking of Articulated Vehicles

Sixu Li,Biao Xu,Manjiang Hu(),Yougang Bian,Xiaolong Sun Ning Chen   

  1. College of Mechanical and Vehicle Engineering,Hunan University,State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Changsha 410082
  • Received:2021-02-24 Revised:2021-04-23 Online:2021-08-25 Published:2021-08-20
  • Contact: Manjiang Hu E-mail:manjiang_h@hnu.edu.cn

摘要:

现有的铰接车辆路径跟踪控制方法在模型线性化和预瞄误差过程均产生较大误差,导致跟踪精度降低。针对铰接车辆路径跟踪控制,构建了铰接车辆动力学模型,采用基于状态轨迹的线性化方法补偿动力学误差,提出了考虑路径多点预瞄误差的控制目标,设计了基于动力学模型的模型预测控制器,用以优化铰接点处转向力矩。为验证该方法的有效性,采用Matlab/Simulink和Adams软件构建了联合仿真平台,对控制算法进行了仿真验证。仿真结果表明,本文中设计的控制器可有效提升铰接车辆路径跟踪精度。

关键词: 铰接车辆, 路径跟踪, 模型预测控制, 动力学建模

Abstract:

The existing path tracking control methods have large errors in the process of model linearization and preview, which leads to reduction of tracking accuracy. For path tracking control of articulated vehicles, a dynamic model of articulated vehicles is established.The model is linearized based on state trajectories so that the linearization error can be compensated, and the control target considering path multipoint preview errors is proposed. The model predictive controller based on the dynamic model is constructed to optimize the steering torque at the hinge point. To verify the effectiveness of the method, the joint simulation platform by Matlab/Simulink and Adams software is built for control verification by conducting simulation experiments. The results show that the controller designed can effectively improve path tracking accuracy for articulated vehicles.

Key words: articulated vehicles, path tracking, model predictive control, dynamic modeling