Fixed-time synchronization of neural networks with time delay via quantized intermittent control

Yang, W; Huang, J; Wen, S; He, X

Fixed-time synchronization of neural networks with time delay via quantized intermittent control

Yang, W Huang, J Wen, S

He, X

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Publisher:: Wiley
Publication Type:: Journal Article
Citation:: Asian Journal of Control, 2022
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Yang, W
dc.contributor.author	Huang, J
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	He, X
dc.date.accessioned	2023-01-30T07:21:38Z
dc.date.available	2023-01-30T07:21:38Z
dc.date.issued	2022-01-01
dc.identifier.citation	Asian Journal of Control, 2022
dc.identifier.issn	1561-8625
dc.identifier.issn	1934-6093
dc.identifier.uri	http://hdl.handle.net/10453/165613
dc.description.abstract	This paper presents an approach for fixed-time synchronization (FIXTS) of neural networks (NNs) by designing quantized intermittent controller. Under the intermittent controller, the synchronization between neural network systems with time delay can be realized. Based on intermittent strategy, FIXTs theory is proposed, and a sufficient condition is established to realize the FIXTS of the master–slave NNs. At the same time, the establishment time of FIXTS is estimated. Finally, the simulation of Gilli attractor to prove the validity of the proposed method.
dc.language	en
dc.publisher	Wiley
dc.relation.ispartof	Asian Journal of Control
dc.relation.isbasedon	10.1002/asjc.2805
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering, 0910 Manufacturing Engineering, 0913 Mechanical Engineering
dc.subject.classification	Industrial Engineering & Automation
dc.title	Fixed-time synchronization of neural networks with time delay via quantized intermittent control
dc.type	Journal Article
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	0910 Manufacturing Engineering
utslib.for	0913 Mechanical Engineering
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	*
dc.date.updated	2023-01-30T07:21:04Z
pubs.publication-status	Published

Abstract:

This paper presents an approach for fixed-time synchronization (FIXTS) of neural networks (NNs) by designing quantized intermittent controller. Under the intermittent controller, the synchronization between neural network systems with time delay can be realized. Based on intermittent strategy, FIXTs theory is proposed, and a sufficient condition is established to realize the FIXTS of the master–slave NNs. At the same time, the establishment time of FIXTS is estimated. Finally, the simulation of Gilli attractor to prove the validity of the proposed method.

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http://hdl.handle.net/10453/165613