期刊首页 优先出版 当期阅读 过刊浏览 作者中心 关于期刊 English

2023年 第18卷 第3期

摘要

关键词

相关研究

回顶部

《机械工程前沿（英文）》 >> 2023年 第18卷 第3期 doi: 10.1007/s11465-023-0753-3

Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Automation, China University of Geosciences, Wuhan 430074, China;3. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

收稿日期： 2022-11-15 发布日期： 2022-11-15
HTML5 PDF 29 收藏 0

下一篇 上一篇

摘要

To achieve the collision-free trajectory tracking of the four-wheeled mobile robot (FMR), existing methods resolve the tracking control and obstacle avoidance separately. Guaranteeing the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is difficult. To address this challenge, this paper proposes an obstacle-circumventing adaptive control (OCAC) framework. Specifically, a novel anti-disturbance terminal slide mode control with adaptive gains is formulated, incorporating specified control laws for different stages. This formulation guarantees rapid convergence and simultaneous chattering elimination. By introducing sub-target points, a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one, thereby reducing the burden of local path searching while ensuring system stability during obstacle circumvention. Comparative experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

相关研究