基于模型预测控制的智能网联汽车路径跟踪控制器设计

doi:10.3901/JME.2019.08.136

机械工程学报 ›› 2019, Vol. 55 ›› Issue (8): 136-144,153.doi: 10.3901/JME.2019.08.136

基于模型预测控制的智能网联汽车路径跟踪控制器设计

王艺¹, 蔡英凤², 陈龙², 王海¹, 何友国², 李健¹

1. 江苏大学汽车与交通工程学院镇江 212013;
2. 江苏大学汽车工程研究院镇江 212013

收稿日期:2018-07-21 修回日期:2018-12-20 出版日期:2019-04-20 发布日期:2019-04-20
通讯作者: 蔡英凤(通信作者),女,1985年出生,博士,副教授,硕士研究生导师。主要研究方向为交通感知与智能车辆。E-mail:caicaixiao0304@126.com
作者简介:王艺,女,1992年出生。主要研究方向为智能车辆转向控制。E-mail:shivery_wang@163.com
基金资助:
国家重点研发计划（2017YFB0102603）、国家自然科学基金（U1564201，U1664258，U1764257，61601203，61773184）、江苏省重点研发计划（BE2016149）、江苏省战略性新兴产业发展重大专项（苏发改高技发（2016）1094号，（2015）1084号）、镇江市重点研发计划（GY2017006）资助项目。

Design of Intelligent and Connected Vehicle Path Tracking Controller Based on Model Predictive Control

WANG Yi¹, CAI Yingfeng², CHEN Long², WANG Hai¹, HE Youguo², LI Jian¹

1. Department of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013;
2. Jiangsu University Automotive Engineering Research Institute, Zhenjiang 212013

Received:2018-07-21 Revised:2018-12-20 Online:2019-04-20 Published:2019-04-20

摘要/Abstract

摘要： 为解决智能车辆的自主转向问题，提高车辆在高速运动过程中的转向精度和稳定性，在智能网联汽车的背景下，从路径跟踪控制出发，提出一种变参数的智能网联汽车路径跟踪控制方法。该方法基于模型预测控制原理，设计了一种智能网联汽车的路径跟踪控制器。该方法先以3自由度模型的车辆模型为控制系统；对系统进行线性化后，确定系统的二次型目标函数，并依据函数形式确定矩阵形式；然后，在Carsim和Matlab/Simulink平台上进行离线仿真，确定各个典型工况下适用于该路径跟踪控制器的仿真参数；最后实现系统可根据由车联网获得车辆实际所处道路形状和实际车速选择合适的路径跟踪控制器的控制参数，完成智能网联汽车的自动转向。仿真结果表明该控制器相对于固定控制参数的控制器具有更好的控制效果，可控制车辆以较高车速行驶时达到较高跟踪精度和行驶稳定性。

关键词: 变参数, 路径跟踪, 模型预测控制, 智能网联汽车

Abstract: In order to solve the problem of autonomous steering of intelligent vehicles and to improve the steering precision and stability during the high-speed movement, and considering the path tracking control, a path tracking control method of variable parameters under the background of intelligent and connected vehicle is proposed. A path tracking controller for intelligent vehicle based on the model predictive control principle is designed. Firstly, a 3-degree-of-freedom dynamic model is considered as the control system. Secondly, a quadratic form cost function of the system is determined after linearizing the system, and the form of the constraints are determined according to the cost function. Thirdly, the controller's parameters for typical operation conditions are obtained with the off-line simulation of the Carsim and Matlab/Simulink platforms. Finally, the intelligent and connected vehicle can complete the automatic steering by selecting the appropriate path tracking control parameters according to the road type where the vehicle is actually located and the actual speed of the vehicle. The simulation results show that the controller has a better control effect than the controller with fixed parameters. This controller can achieve higher tracking accuracy and driving stability when the vehicle is moving at high speed.

Key words: intelligent and connected vehicle, model predictive control, path tracking, variable parameters

中图分类号:

TP242

王艺, 蔡英凤, 陈龙, 王海, 何友国, 李健. 基于模型预测控制的智能网联汽车路径跟踪控制器设计[J]. 机械工程学报, 2019, 55(8): 136-144,153.

WANG Yi, CAI Yingfeng, CHEN Long, WANG Hai, HE Youguo, LI Jian. Design of Intelligent and Connected Vehicle Path Tracking Controller Based on Model Predictive Control[J]. Journal of Mechanical Engineering, 2019, 55(8): 136-144,153.

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基于模型预测控制的智能网联汽车路径跟踪控制器设计

Design of Intelligent and Connected Vehicle Path Tracking Controller Based on Model Predictive Control

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