卡车
航向(导航)
滞后
控制理论(社会学)
汽车工程
理论(学习稳定性)
车辆动力学
计算机科学
汽车操纵
控制工程
控制(管理)
工程类
人工智能
航空航天工程
计算机网络
机器学习
作者
Qiushi Chen,Guangqiang Wu,Qi Zeng,Jianzhuang Zong
标识
DOI:10.4271/02-17-01-0004
摘要
<div>Lateral control is an essential part of driverless mining truck systems. However, the considerable steering lag and poor tracking accuracy limit the development of unmanned mining. In this article, a dynamic preview distance was designed to resist the steering lag. Then the vehicle–road states, which described the real-time lateral and heading errors between the vehicle and the target road, was defined to describe the control strategy more efficiently. In order to trade off the tracking accuracy and stability, the Takagi–Sugeno (TS) fuzzy method was used to adjust the weight matrix of the linear quadratic regulator (LQR) for different vehicle–road states. Based on the actual mine production environment and the TR100 mining truck, experimental results show that the TS-LQR algorithm performed much better than the pure pursuit algorithm.</div>
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