Robotics & Machine Learning Daily News2024,Issue(Mar.7) :49-49.

New Findings in Robotics Described from Beijing Jiaotong University (Prescribed- time Control of Four-wheel Independently Driven Skid-steering Mobile Robots With Prescribed Performance)

Robotics & Machine Learning Daily News2024,Issue(Mar.7) :49-49.

New Findings in Robotics Described from Beijing Jiaotong University (Prescribed- time Control of Four-wheel Independently Driven Skid-steering Mobile Robots With Prescribed Performance)

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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 originating from Beijing, People's Republic o f China, by NewsRx correspondents, research stated, "This paper investigates the trajectory tracking control problem of a four-wheel independently driven skid-s teering mobile robot (FWID-SSMR) while considering friction resistance, paramete r variation and external disturbances. Unlike previous studies that only achieve d stable tracking control of FWID-SSMR, this paper accomplishes prescribed stead y-state and transient performance." Financial support for this research came from Ministry of Education Research in the Humanities and Social Sciences Planning fund. Our news journalists obtained a quote from the research from Beijing Jiaotong Un iversity, "Based on the dynamic model of FWID-SSMR, an integer-order prescribed- time controller (IOPTC) is developed first, which can make the tracking errors c onverge to a predetermined residual set with a preset convergence rate in a pres cribed time. Motivated by it, a fractional-order prescribed-time controller (FOP TC) is developed by exploiting the genetic attenuation properties of fractional calculus (FC) for improving the control performance. The feasibility and effecti veness of the developed controller are verified by Lyapunov theoretical analysis and numerical simulation studies. The simulation results show that both the IOP TC and FOPTC outperform the feedback controller (FBC)."

Key words

Beijing/People's Republic of China/Asi a/Emerging Technologies/Machine Learning/Nano-robot/Robotics/Beijing Jiaoto ng University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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