File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: An LMI-based technique for robust stability analysis of linear systems with polynomial parametric uncertainties

TitleAn LMI-based technique for robust stability analysis of linear systems with polynomial parametric uncertainties
Authors
Issue Date2005
Citation
Lecture Notes In Control And Information Sciences, 2005, v. 312, p. 87-101 How to Cite?
AbstractRobust stability analysis of state space models with respect to real parametric uncertainty is a widely studied challenging problem. In this paper, a quite general uncertainty model is considered, which allows one to consider polynomial nonlinearities in the uncertain parameters. A class of parameter-dependent Lyapunov functions is used to establish stability of a matrix depending polynomially on a vector of parameters constrained in a polytope. Such class, denoted as Homogeneous Polynomially Parameter-Dependent Quadratic Lyapunov Functions (HPD-QLFs), contains quadratic Lyapunov functions whose dependence on the parameters is expressed as a polynomial homogeneous form. Its use is motivated by the property that the considered matricial uncertainty set is stable if and only there exists a HPD-QLF. The paper shows that a sufficient condition for the existence of a HPD-QLF can be derived in terms of Linear Matrix Inequalities (LMIs). © Springer-Verlag Berlin Heidelberg 2005.
Persistent Identifierhttp://hdl.handle.net/10722/155361
ISSN
2005 Impact Factor: 0.269
2015 SCImago Journal Rankings: 0.169
References

 

DC FieldValueLanguage
dc.contributor.authorChesi, Gen_US
dc.contributor.authorGarulli, Aen_US
dc.contributor.authorTesi, Aen_US
dc.contributor.authorVicino, Aen_US
dc.date.accessioned2012-08-08T08:33:04Z-
dc.date.available2012-08-08T08:33:04Z-
dc.date.issued2005en_US
dc.identifier.citationLecture Notes In Control And Information Sciences, 2005, v. 312, p. 87-101en_US
dc.identifier.issn0170-8643en_US
dc.identifier.urihttp://hdl.handle.net/10722/155361-
dc.description.abstractRobust stability analysis of state space models with respect to real parametric uncertainty is a widely studied challenging problem. In this paper, a quite general uncertainty model is considered, which allows one to consider polynomial nonlinearities in the uncertain parameters. A class of parameter-dependent Lyapunov functions is used to establish stability of a matrix depending polynomially on a vector of parameters constrained in a polytope. Such class, denoted as Homogeneous Polynomially Parameter-Dependent Quadratic Lyapunov Functions (HPD-QLFs), contains quadratic Lyapunov functions whose dependence on the parameters is expressed as a polynomial homogeneous form. Its use is motivated by the property that the considered matricial uncertainty set is stable if and only there exists a HPD-QLF. The paper shows that a sufficient condition for the existence of a HPD-QLF can be derived in terms of Linear Matrix Inequalities (LMIs). © Springer-Verlag Berlin Heidelberg 2005.en_US
dc.languageengen_US
dc.relation.ispartofLecture Notes in Control and Information Sciencesen_US
dc.titleAn LMI-based technique for robust stability analysis of linear systems with polynomial parametric uncertaintiesen_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.scopuseid_2-s2.0-33947523985en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33947523985&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume312en_US
dc.identifier.spage87en_US
dc.identifier.epage101en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridChesi, G=7006328614en_US
dc.identifier.scopusauthoridGarulli, A=7003697493en_US
dc.identifier.scopusauthoridTesi, A=7007124648en_US
dc.identifier.scopusauthoridVicino, A=7006250298en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats