汽车工程 ›› 2023, Vol. 45 ›› Issue (4): 579-587.doi: 10.19562/j.chinasae.qcgc.2023.04.006

所属专题: 智能网联汽车技术专题-规划&决策2023年

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混动履带式无人平台轨迹跟踪控制研究

张彬,邹渊(),张旭东,孙逢春,吴喆,孟逸豪   

  1. 1.北京理工大学机械与车辆学院,北京  100081
    2.电动车辆国家工程技术研究中心,北京  100081
  • 收稿日期:2022-05-18 修回日期:2022-06-10 出版日期:2023-04-25 发布日期:2023-04-19
  • 通讯作者: 邹渊 E-mail:zouyuanbit@vip.163.com

Research on Trajectory Tracking Control of Hybrid Tracked Unmanned Platform

Bin Zhang,Yuan Zou(),Xudong Zhang,Fengchun Sun,Zhe Wu,Yihao Meng   

  1. 1.School of Mechanical Engineering,Beijing Institute of Technology,Beijing  100081
    2.National Engineering Research Center of Electric Vehicles,Beijing  100081
  • Received:2022-05-18 Revised:2022-06-10 Online:2023-04-25 Published:2023-04-19
  • Contact: Yuan Zou E-mail:zouyuanbit@vip.163.com

摘要:

为了提高履带式无人平台的轨迹跟踪性能,提出了一种考虑纵向速度规划的分层轨迹跟踪算法并进行了联合仿真验证和实车验证。在建立了包含履带的滑移滑转率和质心侧偏角的车辆运动微分方程的基础上,完成分层轨迹跟踪算法框架的构建。上层基于伪谱法的速度规划算法根据路面信息进行纵向速度规划,并将规划的速度作为目标车速下发给下层基于线性时变模型预测控制(LTV-MPC)的轨迹跟踪算法。基于LTV-MPC的算法通过建立预测模型和约束条件,二次规划求解出两侧电机的目标转速。通过Matlab/Simulink和RecurDyn的联合仿真以及实车验证了所提出的算法在不同地面条件下具有良好的轨迹效果。

关键词: 履带式无人平台, 分层轨迹跟踪算法, 纵向速度规划, 滑移滑转率, 线性时变模型预测控制

Abstract:

To improve the trajectory tracking performance of tracked unmanned platform, a hierarchical trajectory tracking algorithm considering longitudinal speed planning is proposed and verified by co-simulation experiment and real vehicle experiment. Based on the establishment of the vehicle differential equation including the slip ratio of the track and the sideslip angle of the center of mass, the hierarchical trajectory tracking algorithm framework is constructed. Speed planning algorithm of the upper level based on the pseudo spectrum method plans the longitudinal speed according to the road information, and sends the planned speed as the target speed to the lower layer trajectory tracking algorithm based on linear time-varying model predictive control (LTV-MPC). By establishment of the prediction model and constraints, the algorithm based on LTV-MPC solves the target speed of motors on both sides through quadratic programming. Through the real vehicle experiment and the co-simulation of MATLAB/Simulink with RecurDyn, it is verified that the proposed algorithm has good trajectory tracking effect under different ground conditions.

Key words: tracked unmanned platform, hierarchical trajectory tracking algorithm, longitudinal speed planning, slip ratio, linear time-varying model predictive control (LTV-MPC)