Adaptive PI control for H<inf>∞</inf> synchronization of multiple delayed coupled neural networks

Cao, Y; Zhao, L; Zhong, Q; Zhu, S; Guo, Z; Wen, S

Adaptive PI control for H<inf>∞</inf> synchronization of multiple delayed coupled neural networks

Cao, Y Zhao, L Zhong, Q Zhu, S Guo, Z Wen, S

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Neurocomputing, 2023, 560
Issue Date:: 2023-12-01

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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	Zhu, S
dc.contributor.author	Guo, Z
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2024-01-16T21:11:46Z
dc.date.available	2024-01-16T21:11:46Z
dc.date.issued	2023-12-01
dc.identifier.citation	Neurocomputing, 2023, 560
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/174619
dc.description.abstract	This paper focuses on the discussion of H∞ synchronization in multiple state and delayed state coupled neural networks through the implementation of two adaptive proportional–integral (PI) controllers. Firstly, we consider two types of coupled neural networks with multi-weights. Subsequently, we formulate H∞ synchronization criteria using inequality techniques and Lyapunov functional. Furthermore, we address the H∞ synchronization problem for these two networks by employing node-/edge-based adaptive PI controllers. Finally, we validate the effectiveness of the proposed theoretical results through numerical examples.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2023.126855
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	40 Engineering
dc.subject.classification	46 Information and computing sciences
dc.subject.classification	52 Psychology
dc.title	Adaptive PI control for H<inf>∞</inf> synchronization of multiple delayed coupled neural networks
dc.type	Journal Article
utslib.citation.volume	560
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	17 Psychology and Cognitive Sciences
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	2024-01-16T21:11:44Z
pubs.publication-status	Published
pubs.volume	560

Abstract:

This paper focuses on the discussion of H∞ synchronization in multiple state and delayed state coupled neural networks through the implementation of two adaptive proportional–integral (PI) controllers. Firstly, we consider two types of coupled neural networks with multi-weights. Subsequently, we formulate H∞ synchronization criteria using inequality techniques and Lyapunov functional. Furthermore, we address the H∞ synchronization problem for these two networks by employing node-/edge-based adaptive PI controllers. Finally, we validate the effectiveness of the proposed theoretical results through numerical examples.

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http://hdl.handle.net/10453/174619