4.7 Article

Distributed adaptive output feedback containment control for time-delay nonlinear multiagent systems

期刊

AUTOMATICA
卷 127, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2021.109545

关键词

Multiagent systems; Distributed control; Output feedback; Dynamic gain; Time delays; Function approximation

资金

  1. National Research Foundation of Korea (NRF) - Korea government (Ministry of Science and ICT) [2019R1A5A8080290]

向作者/读者索取更多资源

This paper addresses the distributed adaptive containment control problem for uncertain nonlinear multiagent systems with time delays and unmodeled dynamics. By introducing a local reference generator and nonlinear function approximation method, a linear-like distributed adaptive output feedback controller is designed to simplify the controller design. Simulation results illustrate the effectiveness of the proposed method.
This paper addresses the distributed adaptive containment control problem for uncertain nonlinear multiagent systems (MASs) with time delays and unmodeled dynamics under fixed directed graph. With outputs information of neighbors, the local reference generator of each agent is constructed to generate corresponding virtual tracking trajectory belonging to the convex hull spanned by dynamic leaders. Based on the reference generator, we utilize the nonlinear function approximation method and dynamic gain scaling technique to design the linear-like distributed adaptive output feedback controller. The proposed scheme can significantly relax conditions on nonlinearities with time delays, and greatly simplify the controller design procedure. Using a novel lemma, it is proved that the containment errors can converge to an arbitrarily small compact set and the resulting closed-loop system is semi-globally stable. In addition, if uncertain nonlinearities can be modeled as the product of unknown constant parameters and known functions, the global containment control can be achieved. Finally, simulation results are given to illustrate the effectiveness of proposed method. (C) 2021 The Author(s). Published by Elsevier Ltd.

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