Robotics & Machine Learning Daily News2024,Issue(Jun.25) :15-15.

Findings from Guangdong University of Technology in the Area of Robotics Describ ed (Observer-based Neural Control of n-link Flexible-joint Robots)

广东工业大学在机器人领域的研究成果描述(基于观测器的n连杆柔性关节机器人神经控制)

Robotics & Machine Learning Daily News2024,Issue(Jun.25) :15-15.

Findings from Guangdong University of Technology in the Area of Robotics Describ ed (Observer-based Neural Control of n-link Flexible-joint Robots)

广东工业大学在机器人领域的研究成果描述(基于观测器的n连杆柔性关节机器人神经控制)

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-关于机器人的最新研究结果已经发表。根据NewsRx记者从广州发回的新闻报道,研究表明:“本文主要研究了N连杆柔性关节电驱动机器人的自适应神经控制方法,所提出的控制方法只需要了解柔性关节机械手的运动和电枢电流信息。”本研究的资助单位包括国家自然科学基金(NSFC)、国家博士后项目、彭成实验室重点项目、广东省国家自然科学基金、广州科技规划项目。我们的新闻编辑引用了广东工业大学的一篇研究文章:“设计了一个自适应观测器来估计连杆和马达的速度,并应用径向基函数神经网络来估计未知非线性,基于backstepping技术和Lyapunov稳定性理论,”摘要:研究了基于观测器的神经网络控制问题,该问题仅依赖于上行链路事件触发状态,证明了所有信号都是半全局最终一致有界的,跟踪误差可以收敛到零的小邻域内.

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics have been published. According to news reporting originating from Guangzhou, People' s Republic of China, by NewsRx correspondents, research stated, "This article co ncentrates on the adaptive neural control approach of n-link flexible-joint elec trically driven robots. The presented control method only needs to know the posi tion and armature current information of the flexible-joint manipulator." Funders for this research include National Natural Science Foundation of China ( NSFC), China National Postdoctoral Program, Major Key Project of Peng Cheng Labo ratory, National Natural Science Foundation of Guangdong Province, Guangzhou Sci ence and Technology Planning Project. Our news editors obtained a quote from the research from the Guangdong Universit y of Technology, "An adaptive observer is designed to estimate the velocities of links and motors, and radial basis function neural networks are applied to appr oximate the unknown nonlinearities. Based on the backstepping technique and the Lyapunov stability theory, the observer-based neural control issue is addressed by relying on uplink-event-triggered states only. It is demonstrated that all si gnals are semi-globally ultimately uniformly bounded and the tracking errors can converge to a small neighborhood of zero."

Key words

Guangzhou/People's Republic of China/A sia/Emerging Technologies/Machine Learning/Nano-robot/Robotics/Guangdong Un iversity of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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