Article: Hilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems

File Download
  • No File Attached
Links for fulltext
(May Require Subscription)
Supplementary
  • Basic View
  • Metadata View
  • XML View
TitleHilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems
AuthorsWang, Q1 2
Zhong, T3
Wong, N1
Wang, Q3
KeywordsGradient
Hilbert-Schmidt-Hankel Norm
Matrix Second-Order Linear System
Model Reduction
Issue Date2011
PublisherHuanan Ligong Daxue. The Journal's web site is located at http://jcta.alljournals.ac.cn/cta_en/ch/index.aspx
CitationJournal Of Control Theory And Applications, 2011, v. 9 n. 4, p. 571-578 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11768-011-9300-6
AbstractThis paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique. © 2011 South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.
DescriptionThe article can be viewed at http://jcta.alljournals.ac.cn/cta_en/ch/reader/view_abstract.aspx?file_no=JCTA09300&flag=1
ISSN1672-6340
2011 SCImago Journal Rankings: 0.034
DOIhttp://dx.doi.org/10.1007/s11768-011-9300-6
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorWang, Q
dc.contributor.authorZhong, T
dc.contributor.authorWong, N
dc.contributor.authorWang, Q
dc.date.accessioned2012-08-08T08:34:52Z
dc.date.available2012-08-08T08:34:52Z
dc.date.issued2011
dc.description.abstractThis paper considers the optimal model reduction problem of matrix second-order linear systems in the sense of Hilbert-Schmidt-Hankel norm, with the reduced order systems preserving the structure of the original systems. The expressions of the error function and its gradient are derived. Two numerical examples are given to illustrate the presented model reduction technique. © 2011 South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.
dc.description.natureLink_to_subscribed_fulltext
dc.descriptionThe article can be viewed at http://jcta.alljournals.ac.cn/cta_en/ch/reader/view_abstract.aspx?file_no=JCTA09300&flag=1
dc.identifier.citationJournal Of Control Theory And Applications, 2011, v. 9 n. 4, p. 571-578 [How to Cite?]
DOI: http://dx.doi.org/10.1007/s11768-011-9300-6
dc.identifier.citeulike10085215
dc.identifier.doihttp://dx.doi.org/10.1007/s11768-011-9300-6
dc.identifier.epage578
dc.identifier.hkuros209138
dc.identifier.issn1672-6340
2011 SCImago Journal Rankings: 0.034
dc.identifier.issue4
dc.identifier.scopuseid_2-s2.0-81855183292
dc.identifier.spage571
dc.identifier.urihttp://hdl.handle.net/10722/155699
dc.identifier.volume9
dc.languageeng
dc.publisherHuanan Ligong Daxue. The Journal's web site is located at http://jcta.alljournals.ac.cn/cta_en/ch/index.aspx
dc.publisher.placeChina
dc.relation.ispartofJournal of Control Theory and Applications
dc.relation.referencesReferences in Scopus
dc.subjectGradient
dc.subjectHilbert-Schmidt-Hankel Norm
dc.subjectMatrix Second-Order Linear System
dc.subjectModel Reduction
dc.titleHilbert-Schmidt-Hankel norm model reduction for matrix second-order linear systems
dc.typeArticle
Author Affiliations
  1. The University of Hong Kong
  2. Sun Yat-Sen University
  3. South China University of Technology