首页|Finite-time composite learning control for nonlinear teleoperation systems under networked time-varying delays

Finite-time composite learning control for nonlinear teleoperation systems under networked time-varying delays

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The robust finite-time synchronization control problem is investigated for master-slave networked nonlinear telerobotics systems(NNTSs)in this article.Although there have been some research achievements on finite-time control for the NNTSs,these studies are based on the strong assumptions of communication time delays or can only achieve finite-time bounded convergence even when the external forces are zero.Accordingly and in view of the importance of these issues,a novel robust composite learning adaptive control scheme rendering the finite-time master-slave synchronization is proposed in this paper.In particular,the influence of time delays on finite-time convergence of the system is analyzed by employing the multi-dimension finite-time small-gain framework.Meanwhile,in order to achieve accurate and fast estimation of uncertain parameters of the system,both the online historical and the instantaneous data of the estimation data are explored to derive the new parameter adaptive law under a more realizable interval-excitation(IE)condition.Therefore,the convergence of the position/force synchronization errors and the adaptive parameter estimation errors is obtained in finite time,and enhanced robustness of the closed-loop system will also be ensured.Finally,the superior performance of the proposed control algorithms is validated by numerical simulations and hardware experiments.

networked teleoperation systemsfinite-time controlexact parameter estimationsmall-gain theoremunknown communication delays

Yana YANG、Huixin JIANG、Changchun HUA、Junpeng LI

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Institute of Electrical Engineering,Yanshan University,Qinhuangdao 066004,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Hebei ProvinceNatural Science Foundation of Hebei ProvinceNatural Science Foundation of Hebei ProvinceNatural Science Foundation of Hebei ProvinceProvincial Key Laboratory Performance Subsidy Project

623733196193300962073276F2022203036F2021203109F2021203054F202220302522567612H

2024

10.1007/s11432-023-3931-0

中国科学:信息科学(英文版)
中国科学院

中国科学:信息科学(英文版)

CSTPCDEI
影响因子：0.715
ISSN：1674-733X
年,卷(期)：2024.67(6)
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