现代制造工程 ›› 2024, Vol. 531 ›› Issue (12): 77-86.doi: 10.16731/j.cnki.1671-3133.2024.12.010

• 车辆工程制造技术 • 上一篇    下一篇

动态参数自适应的无人驾驶车辆变道跟踪控制*

高爱云1, 勾王启1, 付主木2   

  1. 1 河南科技大学车辆与交通工程学院,洛阳 471000;
    2 河南科技大学信息工程学院,洛阳 471000
  • 收稿日期:2024-03-29 出版日期:2024-12-18 发布日期:2024-12-24
  • 通讯作者: 勾王启,硕士研究生,主要研究方向为无人驾驶车辆控制。
  • 作者简介:高爱云,博士,教授,主要研究方向为混合动力汽车能量管理与协调控制、动力耦合系统分析与设计以及无人驾驶车辆控制。付主木,博士,教授,博士生导师,主要研究方向为机器视觉及其在工业检测中的应用,切换系统、时滞系统的建模、分析与优化,电动汽车能源管理控制策略。E-mail:jessie_wangqi@163.com
  • 基金资助:
    *国家自然科学基金项目(62371182);中原科技创新领军人才项目(194200510012)

Dynamic parameter adaptive control for lane change tracking of driverless vehicles

GAO Aiyun1, GOU Wangqi1, FU Zhumu2   

  1. 1 School of Vehicle and Traffic Engineering,Henan University of Science and Technology, Luoyang 471000,China;
    2 School of Information Engineering,Henan University of Science and Technology, Luoyang 471000,China
  • Received:2024-03-29 Online:2024-12-18 Published:2024-12-24

摘要: 为解决无人驾驶车辆轨迹跟踪精度和控制稳定性问题,提出了一种考虑前馈控制和动态调整速度比例、积分、微分(Proportional Integral Derivative,PID)控制器参数的方法。采用七次多项式进行变道轨迹规划,改进纵向位置和速度双PID控制器,动态调整纵向位移误差,并采用模糊控制对PID控制器参数进行实时整定;同时,结合基于“前馈+反馈”的线性二次型调节器(Linear Quadratic Regulator,LQR)控制算法求解横向位移误差和车身横摆角速度误差,使跟踪误差收敛,最终通过电机模型将控制量转化为期望前轮转角,解决了模型失配导致的横向位移误差较大的问题。进行仿真验证,当车辆以60 km/h的速度在城市道路场景下变道行驶时,横向位移误差控制在0.015 m范围内,纵向位移误差控制在毫米级别,误差范围控制在[0.002,0.006] m,车身横摆角速度变化平稳且横摆角速度误差不超过0.83 rad/s。在此基础上,进一步完成了实车实验,仿真与实车实验结果均表明,所设计的控制器可以达到轨迹跟踪中对高精度的要求,能够保证无人驾驶车辆在变道工况平稳行驶。

关键词: 无人驾驶, 参数自适应, 比例、积分、微分, 模糊控制, 线性二次型调节器, 轨迹跟踪

Abstract: To solve the problem of trajectory tracking accuracy and control stability of driverless vehicles, a method that considers feedforward control and dynamically adjusts speed PID controller parameters is proposed. Seven polynomial is used for lane change trajectory planning, the double PID controller of longitudinal position and speed is improved, the longitudinal displacement error is adjusted dynamically, and the PID parameters are adjusted in real time. Meanwhile, the lateral displacement error and the pendulum velocity error are solved, making the tracking error converge, and finally the control amount is converted into the desired front wheel angle through the motor model, thus solving the problem of large lateral tracking error caused by the model mismatch. By simulation verification, when the vehicle is running in the urban road scene at 60 km/h, the transverse displacement error is controlled within 0.015 m, the longitudinal displacement error is controlled at mm level, and the error range is controlled at [0.002,0.006] m. The speed of the body is stable and the speed error is not more than 0.83 rad/s. On this basis, the real vehicle experiment is further completed. The results of both simulation and real vehicle experiment show that the designed controller can meet the requirements of high precision in trajectory tracking and ensure the smooth driving of driverless vehicles in the lane change condition.

Key words: unmanned driving, parameter-adaptive, Proportional Integral Derivative(PID), fuzzy control, Linear Quadratic Regulator(LQR), trajectory tracking

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