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Article: Robust stochastic stability of genetic regulatory networks with time delays and parametric uncertainties

TitleRobust stochastic stability of genetic regulatory networks with time delays and parametric uncertainties
Authors
KeywordsGenetic regulatory networks
Parametric uncertainties
Square matrix representation (SMR)
Stochastic stability
Time delays
Issue Date2011
PublisherChinese Automatic Control Society. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1561-8625
Citation
Asian Journal Of Control, 2011, v. 13 n. 5, p. 635-644 How to Cite?
AbstractThis paper investigates robust stochastic stability of uncertain genetic regulatory networks. It is assumed that the networks have SUM regulatory functions affected by Wiener processes, time delays and parametric uncertainties. Contrary to existing works, the uncertainty is not restricted to belong to a polytope, but more generally it is assumed to belong to a multi-dimensional set described by polynomial inequalities. First, it is shown that a condition for robust stochastic stability with guaranteed disturbance attenuation for all admissible uncertainties in the absence of time delays can be obtained by solving a convex optimization problem built by exploiting the square matrix representation (SMR) of matrix polynomials and by introducing polynomially parameter-dependent Lyapunov functions. Then, it is shown how this condition can be extended to deal with the presence of time delays with bounded variation rates by introducing polynomially parameter-dependent Lyapunov-Krasovskii functionals (LKFs). Examples with fictitious and real biological models illustrate the use of the proposed methodology. © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society.
Persistent Identifierhttp://hdl.handle.net/10722/135118
ISSN
2023 Impact Factor: 2.7
2023 SCImago Journal Rankings: 0.677
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Jen_HK
dc.contributor.authorChesi, Gen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2011-07-27T01:28:30Z-
dc.date.available2011-07-27T01:28:30Z-
dc.date.issued2011en_HK
dc.identifier.citationAsian Journal Of Control, 2011, v. 13 n. 5, p. 635-644en_HK
dc.identifier.issn1561-8625en_HK
dc.identifier.urihttp://hdl.handle.net/10722/135118-
dc.description.abstractThis paper investigates robust stochastic stability of uncertain genetic regulatory networks. It is assumed that the networks have SUM regulatory functions affected by Wiener processes, time delays and parametric uncertainties. Contrary to existing works, the uncertainty is not restricted to belong to a polytope, but more generally it is assumed to belong to a multi-dimensional set described by polynomial inequalities. First, it is shown that a condition for robust stochastic stability with guaranteed disturbance attenuation for all admissible uncertainties in the absence of time delays can be obtained by solving a convex optimization problem built by exploiting the square matrix representation (SMR) of matrix polynomials and by introducing polynomially parameter-dependent Lyapunov functions. Then, it is shown how this condition can be extended to deal with the presence of time delays with bounded variation rates by introducing polynomially parameter-dependent Lyapunov-Krasovskii functionals (LKFs). Examples with fictitious and real biological models illustrate the use of the proposed methodology. © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society.en_HK
dc.languageengen_US
dc.publisherChinese Automatic Control Society. The Journal's web site is located at http://www.wiley.com/bw/journal.asp?ref=1561-8625-
dc.relation.ispartofAsian Journal of Controlen_HK
dc.subjectGenetic regulatory networksen_HK
dc.subjectParametric uncertaintiesen_HK
dc.subjectSquare matrix representation (SMR)en_HK
dc.subjectStochastic stabilityen_HK
dc.subjectTime delaysen_HK
dc.titleRobust stochastic stability of genetic regulatory networks with time delays and parametric uncertaintiesen_HK
dc.typeArticleen_HK
dc.identifier.emailChesi, G:chesi@eee.hku.hken_HK
dc.identifier.emailHung, YS:yshung@eee.hku.hken_HK
dc.identifier.authorityChesi, G=rp00100en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/asjc.337en_HK
dc.identifier.scopuseid_2-s2.0-84862958868-
dc.identifier.hkuros187531en_US
dc.identifier.hkuros201216-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84856135720&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume13en_HK
dc.identifier.issue5en_HK
dc.identifier.spage635en_HK
dc.identifier.epage644en_HK
dc.identifier.isiWOS:000294977200005-
dc.publisher.placeTaiwanen_HK
dc.identifier.scopusauthoridLi, J=54919601000en_HK
dc.identifier.scopusauthoridChesi, G=7006328614en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK
dc.identifier.issnl1561-8625-

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