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汽车安全与节能学报 ›› 2022, Vol. 13 ›› Issue (1): 112-121.DOI: 10.3969/j.issn.1674-8484.2022.01.011

• 智能驾驶与智慧交通 • 上一篇    下一篇

基于扩张状态观测器的智能汽车弯道轨迹跟踪控制

赵树恩(), 陈文斌, 邓召学, 刘伟   

  1. 重庆交通大学 机电与车辆工程学院,重庆 400074,中国
  • 收稿日期:2021-07-14 修回日期:2021-10-18 出版日期:2022-03-31 发布日期:2022-04-02
  • 作者简介:赵树恩(1972–),男(汉族),陕西,教授。E-mail:zse0916@163.com
  • 基金资助:
    国家自然科学基金资助项目(52072054);道路交通安全公安部重点实验室开放基金项目(2021ZDSYSKFKT08)

Trajectory tracking control for intelligent vehicles driving in curved road based on expanded state observers

ZHAO Shuen(), CHEN Wenbin, DENG Zhaoxue, LIU Wei   

  1. School of Mechatronics and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China
  • Received:2021-07-14 Revised:2021-10-18 Online:2022-03-31 Published:2022-04-02

摘要:

为了提高智能车辆在复杂弯曲道路下进行跟踪控制的精度和稳定性,提出了一种基于扩张状态观测器的模型预测多目标优化控制方法。引入扩张状态观测器实时估计车辆跟踪过程中的总干扰,并对观测器稳定性进行证明;结合模型预测控制实现预测时域内多目标优化效果,利用估计的干扰值对控制量进行前馈补偿,得到车辆在动态干扰下的最优控制量。结果表明:在不同车速和路面附着因数工况下,横向位置误差均方根不超过0.11 m,最大前轮转角量不超过85 mrad,横摆角速度最大值不超过368 mrad。因此,该方法在复杂弯道情况下有较好的跟踪精确性、行驶稳定性和鲁棒性。

关键词: 智能汽车, 弯曲道路行驶, 轨迹跟踪, 扩张状态观测器, 模型预测控制

Abstract:

A model prediction multi-objective optimal control method was proposed based on extended state observer for tracking control of intelligent vehicles driving on complex curved roads to improve tracking accuracy and driving stability. To prove the observer’ stability, the extended state observer was used to estimate the total disturbance of vehicle tracking in real time. Combined with model predictive control, the multi-objective optimization effect was realized in prediction domain, and the estimated disturbance value was used to compensate feedforward for the control quantity, and the optimal control quantity was obtained under dynamic disturbance. The results show that the lateral location root mean square error is less than 0.11 m, the maximum front wheel angle is less than 85 mrad, and the maximum yaw speed is less than 368 mrad under different vehicle speeds and different road adhesion coefficients. Therefore, this method has good tracking accuracy, driving stability and robustness when driving on complex road curves.

Key words: intelligent vehicles, driving in curved road, trajectory tracking, extended state observer, model predictive control

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