File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Convergent algorithms for frequency weighted L 2 model reduction

TitleConvergent algorithms for frequency weighted L 2 model reduction
Authors
KeywordsKalman Filters
L 2 Norm
Linear Systems
Model Reduction
Optimization
Issue Date1997
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/sysconle
Citation
Systems And Control Letters, 1997, v. 31 n. 1, p. 11-20 How to Cite?
AbstractThis paper is concerned with computing an L 2-optimal reduced-order model for a given stable multivariable linear system in the presence of input and output frequency weightings. By parametrizing a class of reduced-order models in terms of an orthogonal projection and using manifold techniques as tools, both continuous and iterative algorithms are derived and their convergence properties are established. As an application, we show that an L 2 optimal reduced-order filter in the closed-loop sense can be computed using these algorithms. © 1997 Elsevier Science B.V.
Persistent Identifierhttp://hdl.handle.net/10722/156462
ISSN
2015 Impact Factor: 1.908
2015 SCImago Journal Rankings: 2.323
References

 

DC FieldValueLanguage
dc.contributor.authorYan, WYen_US
dc.contributor.authorXie, Len_US
dc.contributor.authorLam, Jen_US
dc.date.accessioned2012-08-08T08:42:31Z-
dc.date.available2012-08-08T08:42:31Z-
dc.date.issued1997en_US
dc.identifier.citationSystems And Control Letters, 1997, v. 31 n. 1, p. 11-20en_US
dc.identifier.issn0167-6911en_US
dc.identifier.urihttp://hdl.handle.net/10722/156462-
dc.description.abstractThis paper is concerned with computing an L 2-optimal reduced-order model for a given stable multivariable linear system in the presence of input and output frequency weightings. By parametrizing a class of reduced-order models in terms of an orthogonal projection and using manifold techniques as tools, both continuous and iterative algorithms are derived and their convergence properties are established. As an application, we show that an L 2 optimal reduced-order filter in the closed-loop sense can be computed using these algorithms. © 1997 Elsevier Science B.V.en_US
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/sysconleen_US
dc.relation.ispartofSystems and Control Lettersen_US
dc.subjectKalman Filtersen_US
dc.subjectL 2 Normen_US
dc.subjectLinear Systemsen_US
dc.subjectModel Reductionen_US
dc.subjectOptimizationen_US
dc.titleConvergent algorithms for frequency weighted L 2 model reductionen_US
dc.typeArticleen_US
dc.identifier.emailLam, J:james.lam@hku.hken_US
dc.identifier.authorityLam, J=rp00133en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0031169655en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0031169655&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume31en_US
dc.identifier.issue1en_US
dc.identifier.spage11en_US
dc.identifier.epage20en_US
dc.publisher.placeNetherlandsen_US
dc.identifier.scopusauthoridYan, WY=7402221751en_US
dc.identifier.scopusauthoridXie, L=35087158600en_US
dc.identifier.scopusauthoridLam, J=7201973414en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats