铲子
控制器(灌溉)
控制理论(社会学)
MATLAB语言
跟踪(教育)
控制工程
网络爬虫
模糊逻辑
计算机科学
运动学
工程类
控制(管理)
人工智能
操作系统
万维网
物理
生物
机械工程
经典力学
教育学
心理学
农学
作者
Guohua Wu,Guo Qiang Wang,Qiushi Bi,Yongpeng Wang,Y. Fang,G. Guo,Wentao Qu
摘要
Abstract This paper proposes a path tracking control method combining pure tracking algorithms and self‐adaptive fuzzy control for autonomous driving of an unmanned electric shovel. An improved pure tracking controller was designed based on the kinematic model of heavy crawler taking both the value of deviation and its variation as inputs with the crawler speed on each side as output. The proposed controller and MPC algorithm were simulated using MATLAB for comparison. The results show that the proposed controller has more anthropomorphic characteristics than the MPC method. To verify the actual control effect of the controller, experiments were carried out using a prototype electric shovel for different working conditions. The experimental results proved that the controller is able to meet the control requirements for unmanned electric shovel path tracking.
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