Stochastic distribution synchronization and pinning control for complex heterogeneous dynamical networks

Wang, G; Ji, J; Zhou, J

Stochastic distribution synchronization and pinning control for complex heterogeneous dynamical networks

Wang, G Ji, J

Zhou, J

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Publisher:: WILEY
Publication Type:: Journal Article
Citation:: Asian Journal of Control, 2020, 22, (4), pp. 1547-1564
Issue Date:: 2020-07-01

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Field	Value	Language
dc.contributor.author	Wang, G
dc.contributor.author	Ji, J https://orcid.org/0000-0003-3280-5463
dc.contributor.author	Zhou, J
dc.date.accessioned	2021-03-10T05:17:42Z
dc.date.available	2021-03-10T05:17:42Z
dc.date.issued	2020-07-01
dc.identifier.citation	Asian Journal of Control, 2020, 22, (4), pp. 1547-1564
dc.identifier.issn	1561-8625
dc.identifier.issn	1934-6093
dc.identifier.uri	http://hdl.handle.net/10453/146990
dc.description.abstract	© 2019 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd This paper investigates the stochastic synchronization and pinning control in the sense of probability distribution for a general model of complex heterogeneous dynamical networks subjected to stochastic disturbances. Some generic stochastic synchronization criteria are established for both cases of undirected and directed topology by using the ergodic theory on stochastic dynamical systems. Compared with most existing studies on the stochastic synchronization in the sense of mean square, it is demonstrated that the concept of stochastic distribution synchronization can well characterize the realistic structure and essential nature of complex practical stochastic systems. Subsequently, two representative examples of complex heterogeneous dynamical networks, namely coupled stochastic Duffing oscillators and coupled FitzHugh-Nagumo neuron oscillators, are given to illustrate and numerically verify the theoretical results.
dc.language	English
dc.publisher	WILEY
dc.relation.ispartof	Asian Journal of Control
dc.relation.isbasedon	10.1002/asjc.2044
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	Stochastic distribution synchronization and pinning control for complex heterogeneous dynamical networks
dc.type	Journal Article
utslib.citation.volume	22
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/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-03-10T05:17:27Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	22
utslib.citation.issue	4

Abstract:

© 2019 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd This paper investigates the stochastic synchronization and pinning control in the sense of probability distribution for a general model of complex heterogeneous dynamical networks subjected to stochastic disturbances. Some generic stochastic synchronization criteria are established for both cases of undirected and directed topology by using the ergodic theory on stochastic dynamical systems. Compared with most existing studies on the stochastic synchronization in the sense of mean square, it is demonstrated that the concept of stochastic distribution synchronization can well characterize the realistic structure and essential nature of complex practical stochastic systems. Subsequently, two representative examples of complex heterogeneous dynamical networks, namely coupled stochastic Duffing oscillators and coupled FitzHugh-Nagumo neuron oscillators, are given to illustrate and numerically verify the theoretical results.

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http://hdl.handle.net/10453/146990