Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.

Cao, Y; Zhao, L; Zhong, Q; Wen, S; Shi, K; Xiao, J; Huang, T

Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.

Cao, Y Zhao, L Zhong, Q Wen, S

Shi, K Xiao, J Huang, T

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Publisher:: PERGAMON-ELSEVIER SCIENCE LTD
Publication Type:: Journal Article
Citation:: Neural Netw, 2023, 163, pp. 28-39
Issue Date:: 2023-06

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Field	Value	Language
dc.contributor.author	Cao, Y
dc.contributor.author	Zhao, L
dc.contributor.author	Zhong, Q
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Shi, K
dc.contributor.author	Xiao, J
dc.contributor.author	Huang, T
dc.date.accessioned	2024-01-16T21:28:37Z
dc.date.available	2023-03-21
dc.date.available	2024-01-16T21:28:37Z
dc.date.issued	2023-06
dc.identifier.citation	Neural Netw, 2023, 163, pp. 28-39
dc.identifier.issn	0893-6080
dc.identifier.issn	1879-2782
dc.identifier.uri	http://hdl.handle.net/10453/174646
dc.description.abstract	This paper addresses fixed-time output synchronization problems for two types of complex dynamical networks with multi-weights (CDNMWs) by using two types of adaptive control methods. Firstly, complex dynamical networks with multiple state and output couplings are respectively presented. Secondly, several fixed-time output synchronization criteria for these two networks are formulated based on Lyapunov functional and inequality techniques. Thirdly, by employing two types of adaptive control methods, fixed-time output synchronization issues of these two networks are dealt with. At last, the analytical results are verified by two numerical simulations.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	PERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartof	Neural Netw
dc.relation.isbasedon	10.1016/j.neunet.2023.03.032
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4611 Machine learning
dc.subject.classification	4905 Statistics
dc.subject.mesh	Neural Networks, Computer
dc.subject.mesh	Algorithms
dc.subject.mesh	Time Factors
dc.subject.mesh	Algorithms
dc.subject.mesh	Time Factors
dc.subject.mesh	Neural Networks, Computer
dc.subject.mesh	Neural Networks, Computer
dc.subject.mesh	Algorithms
dc.subject.mesh	Time Factors
dc.title	Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.
dc.type	Journal Article
utslib.citation.volume	163
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	*
dc.date.updated	2024-01-16T21:28:36Z
pubs.publication-status	Published
pubs.volume	163

Abstract:

This paper addresses fixed-time output synchronization problems for two types of complex dynamical networks with multi-weights (CDNMWs) by using two types of adaptive control methods. Firstly, complex dynamical networks with multiple state and output couplings are respectively presented. Secondly, several fixed-time output synchronization criteria for these two networks are formulated based on Lyapunov functional and inequality techniques. Thirdly, by employing two types of adaptive control methods, fixed-time output synchronization issues of these two networks are dealt with. At last, the analytical results are verified by two numerical simulations.

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http://hdl.handle.net/10453/174646