dc.creatorGeromel, JC
dc.creatorKorogui, RH
dc.date2008
dc.dateAPR
dc.date2014-11-15T14:03:01Z
dc.date2015-11-26T17:20:11Z
dc.date2014-11-15T14:03:01Z
dc.date2015-11-26T17:20:11Z
dc.date.accessioned2018-03-29T00:07:49Z
dc.date.available2018-03-29T00:07:49Z
dc.identifierAutomatica. Pergamon-elsevier Science Ltd, v. 44, n. 4, n. 937, n. 948, 2008.
dc.identifier0005-1098
dc.identifierWOS:000255218700004
dc.identifier10.1016/j.automatica.2007.08.010
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/79984
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/79984
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/79984
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1283076
dc.descriptionIn this paper a new approach to H-2 robust filter design is proposed. Both continuous- and discrete-time invariant systems subject to polytopic parameter uncertainty are considered. After a brief discussion on some of the most expressive methods available for H-2 robust filter design, a new one based on a performance certificate calculation is presented. The performance certificate is given in terms of the gap produced by the robust filter between lower and upper bounds of a minimax programming problem where the H-2 norm of the estimation error is maximized with respect to the feasible uncertainties and minimized with respect to all linear, rational and causal filters. The calculations are performed through convex programming methods developed to deal with linear matrix inequality (LMI). Many examples borrowed from the literature to date are solved and it is shown that the proposed method outperforms all other designs. (c) 2007 Elsevier Ltd. All rights reserved.
dc.description44
dc.description4
dc.description937
dc.description948
dc.languageen
dc.publisherPergamon-elsevier Science Ltd
dc.publisherOxford
dc.publisherInglaterra
dc.relationAutomatica
dc.relationAutomatica
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectrobust H-2 filtering
dc.subjectconvex programming
dc.subjectKalman filter
dc.subjectfilter design
dc.subjectlinear matrix inequalities (LMIs)
dc.subjectLinear-systems
dc.subjectLmi Characterization
dc.subjectLyapunov Functions
dc.subjectUncertain Systems
dc.subjectStability
dc.titleH-2 robust filter design with performance certificate via convex programming
dc.typeArtículos de revistas


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