Null space-based control with gain modulation applied to a MARV in backward movement

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
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引用次数: 0

Abstract

A controller is proposed to guide a multi-articulated robot vehicle (MARV) moving backwards, following a certain path. The ability to avoid fixed and moving obstacles is included, using the null space-based control technique to manage the conflicting tasks of following a path and avoiding obstacles. Additionally, control gains are modulated, thus reducing the risk of jackknifing. These new approaches are the contributions of the article. Results of laboratory-scale experiments with a MARV pushing one and two trailers are presented and discussed, which validate the proposed controller. Simulation results are also presented considering a MARV with three trailers, showing that the proposed controller can be adopted for larger articulated chains and another experiment that shows that it is possible to avoid moving obstacles.

对后退运动中的 MARV 进行增益调制的空基控制。
本文提出了一种控制器,用于引导多关节机器人车(MARV)按照一定的路径向后移动。其中包括避开固定障碍物和移动障碍物的能力,利用基于空域的控制技术来管理遵循路径和避开障碍物这两项相互冲突的任务。此外,还对控制增益进行了调制,从而降低了发生 "千斤顶断裂 "的风险。这些新方法是本文的贡献所在。文章介绍并讨论了推着一辆和两辆拖车的 MARV 的实验室规模实验结果,这些结果验证了所提出的控制器。此外,文章还介绍了考虑到带有三辆拖车的 MARV 的仿真结果,表明提议的控制器可用于更大的铰接链,并介绍了另一项实验,表明它可以避开移动的障碍物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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