一种自动超扭滑模随墙控制方法

IF 0.4 4区计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI:10.61416/ceai.v25i2.8352

Edgar Martinez, Rafael Murrieta-Cid, Hector Becerra

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引用次数: 0

摘要

本文提出了一种利用激光测距仪测量多边形环境中差动驱动机器人的墙体跟踪方法。我们提出了一种自动机来管理机器人的观测值，并根据自动机中的状态选择控制设定点。我们还提出了一种超扭转滑模控制，可以快速达到控制设定点。这种方法允许机器人连续移动，而不需要在障碍物进入机器人的路径时停下来。这种方法使机器人能够快速而稳健地跟随墙壁。墙跟踪功能可用于探索未知环境或在环境中查找对象。DOI: 10.61416 / ceai.v25i2.8352

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An Automaton and Super-Twisting Sliding-Mode Control for Wall Following

This work proposes an approach for wall following with a differential drive robot in a polygonal environment using laser range finder measurements.We propose an automaton which manages the robot observationsand selects the control set-points according to the state in theautomaton. We also propose a super-twisting sliding-mode control whichrapidly reaches the control set-points.The approach allows the robot to continuously move without the need ofstopping when obstacles get in the path of the robot. Thisapproach allows the robot to following the walls fast and robustly.The wall following capability can be used to explore an unknown environment orto find objects in the environment. DOI: 10.61416/ceai.v25i2.8352

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来源期刊

Control Engineering and Applied Informatics 工程技术-

CiteScore

1.50

自引率

22.20%

发文量

审稿时长

6 months

期刊介绍： The Journal is promoting theoretical and practical results in a large research field of Control Engineering and Technical Informatics. It has been published since 1999 under the Romanian Society of Control Engineering and Technical Informatics coordination, in its quality of IFAC Romanian National Member Organization and it appears quarterly. Each issue has up to 12 papers from various areas such as control theory, computer engineering, and applied informatics. Basic topics included in our Journal since 1999 have been time-invariant control systems, including robustness, stability, time delay aspects; advanced control strategies, including adaptive, predictive, nonlinear, intelligent, multi-model techniques; intelligent control techniques such as fuzzy, neural, genetic algorithms, and expert systems; and discrete event and hybrid systems, networks and embedded systems. Application areas covered have been environmental engineering, power systems, biomedical engineering, industrial and mobile robotics, and manufacturing.