Robotics & Machine Learning Daily News2024,Issue(Oct.31) :153-153.

Studies in the Area of Robotics Reported from Qingdao University of Technology ( Disturbance Observer Based Adaptive Predefinedtime Sliding Mode Control for Rob ot Manipulators With Uncertainties and Disturbances)

Robotics & Machine Learning Daily News2024,Issue(Oct.31) :153-153.

Studies in the Area of Robotics Reported from Qingdao University of Technology ( Disturbance Observer Based Adaptive Predefinedtime Sliding Mode Control for Rob ot Manipulators With Uncertainties and Disturbances)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-A new study on Robotics is now availab le. According to news reporting originating fromQingdao, People's Republic of C hina, by NewsRx correspondents, research stated, "This article developsa predef ined-time sliding mode control approach for systems with external disturbances a nd uncertaintiesthrough a nonlinear disturbance observer (DO). For addressing p redefined-time stabilization problem ofrobotic manipulator system, a predefined -time sliding mode surface is proposed, ensuring system statesconverge to origi n within a predefined-time once sliding mode surface is attained."Financial support for this research came from National Natural Science Foundatio n of China (NSFC).Our news editors obtained a quote from the research from the Qingdao University of Technology,"Compared to conventional fixed-time and finite-time control stra tegies, a distinctive advantage of thisscheme is that system settling time can be explicitly chosen in advance and independent of system states.To achieve pre defined-time performance, a disturbance observer is introduced to generate the d isturbanceestimate, which can be incorporated into controller to counteract dis turbance. To address the systemsuncertainty, an adaptive law is employed to est imate the unknown upper boundary of system uncertainties."

Key words

Qingdao/People's Republic of China/Asi a/Emerging Technologies/Machine Learning/Robot/Robotics/Qingdao University of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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