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dc.contributorDepartment of Computing-
dc.creatorXie, L-
dc.creatorLu, L-
dc.creatorZhang, DD-
dc.creatorZhang, H-
dc.rights© 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectAsymptotic stabilityen_US
dc.subjectiscrete time control systemsen_US
dc.subjectLyapunov methodsen_US
dc.subjectMatrix algebraen_US
dc.subjectSignal filtering and predictionen_US
dc.subjectUncertain systemsen_US
dc.titleRobust filtering for uncertain discrete-time systems : an improved LMI approachen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: David Zhangen_US
dcterms.abstractThis paper discusses the robust filtering problems for linear discrete-time systems with polytopic parameter uncertainty under the H₂ and H[sub ∞] performance. We aim to derive a less conservative design than existing sufficient linear matrix inequality (LMI) based conditions. It is shown that a more efficient evaluation of robust H₂ or H[sub ∞] performance can be obtained by a matrix inequality condition which contains additional free parameters as compared to existing characterizations. When applying this new matrix inequality condition to the robust filter design, these parameters give additional freedoms in optimizing the guaranteed H₂ or H[sub ∞] performance. The optimization will then lead to a less conservative design. The results will recover the existing robust H₂ and H[sub ∞] filtering ones when the additional free parameters are set to be zero. We also propose an iterative algorithm to further refine the suboptimal filter. Examples are given to demonstrate the less conservatism of the proposed approaches.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation42nd IEEE Conference on Decision and Control : December 9-12, 2003, Maui, Hawaii, USA : proceedings, v. 1, p. 906-911-
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