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Article: Estimating the domain of attraction for uncertain polynomial systems

TitleEstimating the domain of attraction for uncertain polynomial systems
Authors
KeywordsDomain Of Attraction
Lmi
Lyapunov Function
Nonlinear Systems
Uncertainty
Issue Date2004
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automatica
Citation
Automatica, 2004, v. 40 n. 11, p. 1981-1986 How to Cite?
AbstractEstimating the Domain of Attraction (DA) of equilibrium points is a problem of fundamental importance in systems engineering. Several approaches have been proposed for the case of known polynomial systems allowing one to find the Largest Estimate of the DA (LEDA) for a given Lyapunov Function (LF). However, the problem of estimating the Robust DA (RDA), that is the DA guaranteed for all possible uncertainties in an uncertain system, it is still an unsolved problem. In this paper, LMI methods are proposed for estimating the RDA in the case of systems depending polynomially in the state and in the uncertainty which is supposed to belong to a polytope. Specifically, the issue of computing the Robust LEDA (RLEDA), that is the intersection of all LEDAs, is considered for common and parameter-dependent LFs, providing constant and parameter-dependent lower bounds. The computation of approximations with simple shape of the RLEDA in the case of parameter-dependent LFs is also discussed. © 2004 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/155472
ISSN
2023 Impact Factor: 4.8
2023 SCImago Journal Rankings: 3.502
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_US
dc.date.accessioned2012-08-08T08:33:40Z-
dc.date.available2012-08-08T08:33:40Z-
dc.date.issued2004en_US
dc.identifier.citationAutomatica, 2004, v. 40 n. 11, p. 1981-1986en_US
dc.identifier.issn0005-1098en_US
dc.identifier.urihttp://hdl.handle.net/10722/155472-
dc.description.abstractEstimating the Domain of Attraction (DA) of equilibrium points is a problem of fundamental importance in systems engineering. Several approaches have been proposed for the case of known polynomial systems allowing one to find the Largest Estimate of the DA (LEDA) for a given Lyapunov Function (LF). However, the problem of estimating the Robust DA (RDA), that is the DA guaranteed for all possible uncertainties in an uncertain system, it is still an unsolved problem. In this paper, LMI methods are proposed for estimating the RDA in the case of systems depending polynomially in the state and in the uncertainty which is supposed to belong to a polytope. Specifically, the issue of computing the Robust LEDA (RLEDA), that is the intersection of all LEDAs, is considered for common and parameter-dependent LFs, providing constant and parameter-dependent lower bounds. The computation of approximations with simple shape of the RLEDA in the case of parameter-dependent LFs is also discussed. © 2004 Elsevier Ltd. All rights reserved.en_US
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/automaticaen_US
dc.relation.ispartofAutomaticaen_US
dc.subjectDomain Of Attractionen_US
dc.subjectLmien_US
dc.subjectLyapunov Functionen_US
dc.subjectNonlinear Systemsen_US
dc.subjectUncertaintyen_US
dc.titleEstimating the domain of attraction for uncertain polynomial systemsen_US
dc.typeArticleen_US
dc.identifier.emailChesi, G:chesi@eee.hku.hken_US
dc.identifier.authorityChesi, G=rp00100en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.automatica.2004.06.014en_US
dc.identifier.scopuseid_2-s2.0-4444352916en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-4444352916&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume40en_US
dc.identifier.issue11en_US
dc.identifier.spage1981en_US
dc.identifier.epage1986en_US
dc.identifier.isiWOS:000224333900015-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridChesi, G=7006328614en_US
dc.identifier.citeulike7787786-
dc.identifier.issnl0005-1098-

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