卡西姆
控制理论(社会学)
控制器(灌溉)
电子稳定控制
偏航
理论(学习稳定性)
跟踪(教育)
扭矩
MATLAB语言
路径(计算)
航向(导航)
力矩(物理)
车辆动力学
工程类
计算机科学
控制(管理)
汽车工程
人工智能
心理学
生物
航空航天工程
教育学
热力学
经典力学
程序设计语言
农学
物理
机器学习
操作系统
作者
Fen Lin,Mingbiao Hao,Minghong Sun,Yuke Chen,Jian Wu,Chengliang Qian
标识
DOI:10.1177/09544070221083728
摘要
In current research of autonomous vehicle path tracking, most contributions focus on tracking accuracy during complex driving condition. However, the vehicle might fall into unstable dangerous condition when the road curvature is big or with high speed. A path tracking control framework is proposed in this paper, which considers path tracking accuracy and vehicle stability. In general, the control framework consists of three main components: vehicle stability judging controller, path tracking controller, and torque distributor. Firstly, the stability of the current vehicle can be evaluated by the stability judgment controller according to the phase plane of the sideslip angle. Then, the proportion of vehicle stability in the control objective is adjusted according to the current vehicle stability. To improve the path tracking accuracy, the path tracking is composed of a combined controller using MPC algorithm, which controls the front wheel angle and direct yaw moment at the same time. After that, the torque distributor is developed to distribute the desired yaw moment into four executive wheels, which synthesizes the results of power performance distribution and stability distribution. Finally, the effectiveness of the proposed control framework is verified by the Matlab-CarSim co-simulation experiment and the hardware-in-the-loop experiment based on LabVIEW-RT. The results show that the proposed controller has better tracking accuracy and stability than the general MPC controller.
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