Findings from University College London (UCL) in the Area of Machine Learning Re ported (Passive Fault-tolerant Augmented Neural Lyapunov Control: a Method To Sy nthesise Control Functions for Marine Vehicles Affected By Actuators Faults)

伦敦大学学院(UCL)在机器学习领域的研究结果(被动容错增强神经李雅普诺夫控制:一种考虑执行器故障影响的船舶控制函数的方法)

Robotics & Machine Learning Daily News2024，Issue(Jul.2) ：84-85.

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Findings from University College London (UCL) in the Area of Machine Learning Re ported (Passive Fault-tolerant Augmented Neural Lyapunov Control: a Method To Sy nthesise Control Functions for Marine Vehicles Affected By Actuators Faults)

伦敦大学学院(UCL)在机器学习领域的研究结果(被动容错增强神经李雅普诺夫控制:一种考虑执行器故障影响的船舶控制函数的方法)

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摘要

由一名新闻记者兼机器人与机器学习每日新闻编辑-研究人员详细介绍了机器学习的新数据。根据NewsRx Jo Urnalists在英国伦敦的新闻报道，研究表明：“执行器故障可以确定控制系统的闭环稳定性。冗余执行器组和容错控制(FTC)策略可以用来增强系统对执行器效率损失、完全故障或干扰的恢复能力。”这项研究的资助者包括南安普顿国家海洋学中心(UK)、伦敦大学学院(UK)、欧洲研究理事会(ERC)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting from London, United Kingdom, by NewsRx jo urnalists, research stated, “Closed-loop stability of control systems can be und ermined by actuator faults. Redundant actuator sets and Fault-Tolerant Control ( FTC) strategies can be exploited to enhance system resiliency to loss of actuato r efficiency, complete failures or jamming.” Funders for this research include National Oceanography Centre, Southampton (UK) , University College London, London (UK), European Research Council (ERC).

Key words

London/United Kingdom/Europe/Cyborgs/Emerging Technologies/Machine Learning/University College London (UCL)

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出版年

2024

Robotics & Machine Learning Daily News

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