Observer-Based Quasi-Synchronization of Delayed Dynamical Networks With Parameter Mismatch Under Impulsive Effect.

Ni, X; Wen, S; Wang, H; Guo, Z; Zhu, S; Huang, T

Observer-Based Quasi-Synchronization of Delayed Dynamical Networks With Parameter Mismatch Under Impulsive Effect.

Ni, X Wen, S

Wang, H Guo, Z Zhu, S Huang, T

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Neural Networks and Learning Systems, 2021, 32, (7), pp. 3046-3055
Issue Date:: 2021-08-03

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Field	Value	Language
dc.contributor.author	Ni, X
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Wang, H
dc.contributor.author	Guo, Z
dc.contributor.author	Zhu, S
dc.contributor.author	Huang, T
dc.date.accessioned	2022-04-27T06:38:01Z
dc.date.available	2022-04-27T06:38:01Z
dc.date.issued	2021-08-03
dc.identifier.citation	IEEE Transactions on Neural Networks and Learning Systems, 2021, 32, (7), pp. 3046-3055
dc.identifier.issn	1045-9227
dc.identifier.issn	2162-2388
dc.identifier.uri	http://hdl.handle.net/10453/156660
dc.description.abstract	This article focuses on the observer-based quasi-synchronization problem of delayed dynamical networks with parameter mismatch under impulsive effect. First, since the state of each node is unknown in the real situation, the state estimation strategy is proposed to estimate the state of each node, so as to design an appropriate synchronization controller. Then, the corresponding controller is constructed to synchronize the slave nodes with their leader node. In this article, we take the impulsive effect into consideration, which means that an impulsive signal will be applied to the system every so often. Due to the existence of parameter mismatch and time-varying delay, by constructing an appropriate Lyapunouv function, we will eventually obtain a differential equation with constant and time-varying delay terms. Then, we analyze its trajectory by introducing the Cauchy matrix and prove its boundedness by contradiction. Finally, a numerical simulation is presented to illustrate the validness of obtained results.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Transactions on Neural Networks and Learning Systems
dc.relation.isbasedon	10.1109/tnnls.2020.3009271
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Observer-Based Quasi-Synchronization of Delayed Dynamical Networks With Parameter Mismatch Under Impulsive Effect.
dc.type	Journal Article
utslib.citation.volume	32
utslib.location.activity	United States
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-04-27T06:38:00Z
pubs.issue	7
pubs.publication-status	Published
pubs.volume	32
utslib.citation.issue	7

Abstract:

This article focuses on the observer-based quasi-synchronization problem of delayed dynamical networks with parameter mismatch under impulsive effect. First, since the state of each node is unknown in the real situation, the state estimation strategy is proposed to estimate the state of each node, so as to design an appropriate synchronization controller. Then, the corresponding controller is constructed to synchronize the slave nodes with their leader node. In this article, we take the impulsive effect into consideration, which means that an impulsive signal will be applied to the system every so often. Due to the existence of parameter mismatch and time-varying delay, by constructing an appropriate Lyapunouv function, we will eventually obtain a differential equation with constant and time-varying delay terms. Then, we analyze its trajectory by introducing the Cauchy matrix and prove its boundedness by contradiction. Finally, a numerical simulation is presented to illustrate the validness of obtained results.

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http://hdl.handle.net/10453/156660