吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (12): 3717-3728.doi: 10.13229/j.cnki.jdxbgxb.20230167

• 通信与控制工程 • 上一篇    下一篇

基于曲率增广的智能车辆轨迹跟踪控制

刘果1,2(),熊坚1(),杨秀建1,何扬帆1   

  1. 1.昆明理工大学 交通工程学院,昆明 650504
    2.昆明理工大学 城市学院,昆明 650051
  • 收稿日期:2023-02-24 出版日期:2024-12-01 发布日期:2025-01-24
  • 通讯作者: 熊坚 E-mail:liuguokust@126.com;xiebox@163.com
  • 作者简介:刘果(1983-),女,博士研究生.研究方向:智能车辆轨迹跟踪和控制.E-mail:liuguokust@126.com
  • 基金资助:
    国家自然科学基金项目(52162046)

Intelligent vehicle trajectory tracking control based on curvature augmentation

Guo LIU1,2(),Jian XIONG1(),Xiu-jian YANG1,Yang-fan HE1   

  1. 1.Faculty of Transportation Engineering,Kunming University of Science and Technology,Kunming 650504,China
    2.City College,Kunming University of Science and Technology,Kunming 650051,China
  • Received:2023-02-24 Online:2024-12-01 Published:2025-01-24
  • Contact: Jian XIONG E-mail:liuguokust@126.com;xiebox@163.com

摘要:

设计了一种带转角补偿的曲率增广模型预测控制+比例积分控制器,以提高智能车辆在非直线参考轨迹下的跟踪精度。首先,基于跟踪偏差车辆模型,将曲率作为增广量设计模型预测控制算法,分析了曲率增广对控制器性能的影响。其次,利用李雅普诺夫直接方法获得保证算法稳定的预测时域,计算了稳态误差,并设计了比例积分控制器补偿前轮转角以消除稳态横向偏差。最后,进行了仿真分析,结果表明:本文所设计的控制器在保证稳定性和平顺性的同时,可提高车辆轨迹的跟踪精度且收敛速度更快,在不同极限稳定条件下也能获得较好的控制效果。

关键词: 自动控制技术, 智能车辆, 轨迹跟踪, 曲率增广模型预测控制, 比例积分控制

Abstract:

In order to improve tracking accuracy of intelligent vehicle under non-linear reference trajectories, a curvature augmentation model predictive control/propotional integral controller with front wheel angle compensation was proposed. First, based on tracking deviation vehicle model, model predictive control algorithm was designed by using curvature as augmentation state, and influence of curvature broadening was analyzed. Then, Lyapunov direct method was used to obtain predictive horizon that ensures algorithm stability, and system steady-state error was calculated. To eliminate steady-state lateral deviation, propotional integral controller was designed to compensate front wheel angle. Finally, simulation was conducted and results show that, the designed controller improves trajectory tracking accuracy and achieves better convergence rate, while ensuring stability and smoothness, and obtains good control effect under limit conditions.

Key words: automatic control technology, intelligent vehicle, trajectory tracking, curvature augmentation model predictive control, propotional integral control

中图分类号: 

  • TP273

图1

单轨二自由度车辆模型及Frenet坐标系"

图2

曲率增广项补偿的前轮转角"

图3

车速对预测时域内的跟踪偏差代价的影响及预测步长的选取"

图4

曲率增广MPC+PI控制器的结构"

表1

仿真用的整车参数"

车辆参数数值
车辆质量m/kg1723
前轴距质心的距离lf/m1.232
后轴距质心的距离lr/m1.468
车辆绕z轴的转动惯量I/(kg·m-24175
前轮侧偏刚度Cαf/(N·rad-1-66900
后轮侧偏刚度Cαr/(N·rad-1-62700
前轮转角约束umin,umax/rad-0.348?8,0.348?8
前轮转角变化量约束Δumin,Δumax/rad-0.017?4,0.017?4

图5

Fishhook轨迹下的仿真结果"

表2

Fishhook轨迹下的横向偏差和航向角偏差的均方根及稳定时间"

控制器横向偏差均方根/m航向角偏差均方根/rad稳定时间/s
预瞄MPC0.02930.001722.647
曲率增广MPC0.00580.000551.379
预瞄MPC+PI0.01580.001132.361
曲率增广MPC+PI0.00130.000491.22

图6

双移线轨迹下的仿真结果"

表3

双移线轨迹下的横向偏差和航向角偏差的均方根"

控制器横向偏差均方根/m航向角偏差均方根/rad
预瞄MPC0.14410.0164
曲率增广MPC0.09320.0136
预瞄MPC+PI0.09470.0137
曲率增广MPC+PI0.05970.0087

表4

不同工况下曲率增广MPC+PI控制器的横向偏差和航向角偏差的均方根"

工况横向偏差均方根/m航向角偏差均方根/rad
车速/(m·s-1附着系数
100.30.02240.0041
150.30.060.0113
250.60.10910.0203
300.80.12770.0234
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