Stability Analysis for Nonlinear Impulsive Control System with Uncertainty Factors.

Ren, Z; Wen, S; Li, Q; Feng, Y; Tang, N

Stability Analysis for Nonlinear Impulsive Control System with Uncertainty Factors.

Ren, Z Wen, S

Li, Q Feng, Y Tang, N

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Publisher:: Hindawi Limited
Publication Type:: Journal Article
Citation:: Computational intelligence and neuroscience, 2020, 2020
Issue Date:: 2020-01

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Field	Value	Language
dc.contributor.author	Ren, Z
dc.contributor.author	Wen, S https://orcid.org/0000-0002-5048-0319
dc.contributor.author	Li, Q
dc.contributor.author	Feng, Y
dc.contributor.author	Tang, N
dc.date.accessioned	2021-03-10T05:47:18Z
dc.date.available	2020-11-06
dc.date.available	2021-03-10T05:47:18Z
dc.date.issued	2020-01
dc.identifier.citation	Computational intelligence and neuroscience, 2020, 2020
dc.identifier.issn	1687-5265
dc.identifier.issn	1687-5273
dc.identifier.uri	http://hdl.handle.net/10453/146994
dc.description.abstract	Considering the limitation of machine and technology, we study the stability for nonlinear impulsive control system with some uncertainty factors, such as the bounded gain error and the parameter uncertainty. A new sufficient condition for this system is established based on the generalized Cauchy-Schwarz inequality in this paper. Compared with some existing results, the proposed method is more practically applicable. The effectiveness of the proposed method is shown by a numerical example.
dc.format	Electronic-eCollection
dc.language	eng
dc.publisher	Hindawi Limited
dc.relation.ispartof	Computational intelligence and neuroscience
dc.relation.isbasedon	10.1155/2020/8818794
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	1109 Neurosciences, 1702 Cognitive Sciences
dc.subject.classification	Neurology & Neurosurgery
dc.title	Stability Analysis for Nonlinear Impulsive Control System with Uncertainty Factors.
dc.type	Journal Article
utslib.citation.volume	2020
utslib.location.activity	United States
utslib.for	1109 Neurosciences
utslib.for	1702 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	open_access	*
pubs.consider-herdc	false
dc.date.updated	2021-03-10T05:47:15Z
pubs.publication-status	Published
pubs.volume	2020

Abstract:

Considering the limitation of machine and technology, we study the stability for nonlinear impulsive control system with some uncertainty factors, such as the bounded gain error and the parameter uncertainty. A new sufficient condition for this system is established based on the generalized Cauchy-Schwarz inequality in this paper. Compared with some existing results, the proposed method is more practically applicable. The effectiveness of the proposed method is shown by a numerical example.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/146994