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Article: Hankel-type model reduction for linear repetitive processes: Differential and discrete cases
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TitleHankel-type model reduction for linear repetitive processes: Differential and discrete cases
 
AuthorsWu, L2
Lam, J1
 
KeywordsLinear Matrix Inequality (Lmi)
Linear Repetitive Processes
Model Reduction
 
Issue Date2008
 
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0923-6082
 
CitationMultidimensional Systems And Signal Processing, 2008, v. 19 n. 1, p. 41-78 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11045-007-0031-2
 
AbstractThis paper investigates a Hankel-type model reduction problem for linear repetitive processes. Both differential and discrete cases are considered. For a given stable along the pass process, our attention is focused on the construction of a reduced-order stable along the pass process, which guarantees the corresponding error process to have a specified Hankel-type error performance. The Hankel-type performances are first established for differential and discrete linear repetitive processes, respectively, and the corresponding model reduction problems are solved by using the projection approach. Since these obtained conditions are not expressed in linear matrix inequality (LMI) form, the cone complementary linearization (CCL) method is exploited to cast them into sequential minimization problems subject to LMI constraints, which can be solved efficiently. Three numerical examples are provided to demonstrate the proposed theory. © 2007 Springer Science+Business Media, LLC.
 
ISSN0923-6082
2012 Impact Factor: 0.857
2012 SCImago Journal Rankings: 0.674
 
DOIhttp://dx.doi.org/10.1007/s11045-007-0031-2
 
ISI Accession Number IDWOS:000252281400003
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorWu, L
 
dc.contributor.authorLam, J
 
dc.date.accessioned2012-08-08T08:44:36Z
 
dc.date.available2012-08-08T08:44:36Z
 
dc.date.issued2008
 
dc.description.abstractThis paper investigates a Hankel-type model reduction problem for linear repetitive processes. Both differential and discrete cases are considered. For a given stable along the pass process, our attention is focused on the construction of a reduced-order stable along the pass process, which guarantees the corresponding error process to have a specified Hankel-type error performance. The Hankel-type performances are first established for differential and discrete linear repetitive processes, respectively, and the corresponding model reduction problems are solved by using the projection approach. Since these obtained conditions are not expressed in linear matrix inequality (LMI) form, the cone complementary linearization (CCL) method is exploited to cast them into sequential minimization problems subject to LMI constraints, which can be solved efficiently. Three numerical examples are provided to demonstrate the proposed theory. © 2007 Springer Science+Business Media, LLC.
 
dc.description.natureLink_to_subscribed_fulltext
 
dc.identifier.citationMultidimensional Systems And Signal Processing, 2008, v. 19 n. 1, p. 41-78 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11045-007-0031-2
 
dc.identifier.doihttp://dx.doi.org/10.1007/s11045-007-0031-2
 
dc.identifier.epage78
 
dc.identifier.isiWOS:000252281400003
 
dc.identifier.issn0923-6082
2012 Impact Factor: 0.857
2012 SCImago Journal Rankings: 0.674
 
dc.identifier.issue1
 
dc.identifier.scopuseid_2-s2.0-38149006262
 
dc.identifier.spage41
 
dc.identifier.urihttp://hdl.handle.net/10722/156935
 
dc.identifier.volume19
 
dc.languageeng
 
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0923-6082
 
dc.publisher.placeUnited States
 
dc.relation.ispartofMultidimensional Systems and Signal Processing
 
dc.relation.referencesReferences in Scopus
 
dc.subjectLinear Matrix Inequality (Lmi)
 
dc.subjectLinear Repetitive Processes
 
dc.subjectModel Reduction
 
dc.titleHankel-type model reduction for linear repetitive processes: Differential and discrete cases
 
dc.typeArticle
 
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Author Affiliations
  1. The University of Hong Kong
  2. South China University of Technology