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Subspace-based Identification of Infinite-dimensional Multivariable Systems from Frequency-response Data
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Marmara Research Centre, Turkey.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1996 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 32, no 6, 885-902 p.Article in journal (Refereed) Published
Abstract [en]

A new identification algorithm which identifies low complexity models of infinite-dimensional systems from equidistant frequency-response data is presented. The new algorithm is a combination of the Fourier transform technique with the recent subspace techniques. Given noisefree data, finite-dimensional systems are exactly retrieved by the algorithm. When noise is present, it is shown that identified models strongly converge to the balanced truncation of the identified system if the measurement errors are covariance bounded. Several conditions are derived on consistency, illustrating the trade-offs in the selection of certain parameters of the algorithm. Two examples are presented which clearly illustrate the good performance of the algorithm.

Place, publisher, year, edition, pages
Elsevier, 1996. Vol. 32, no 6, 885-902 p.
Keyword [en]
System identification, Frequency-response data, Infinite-dimensional systems, State-space models
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56358DOI: 10.1016/0005-1098(96)00022-2OAI: oai:DiVA.org:liu-56358DiVA: diva2:318591
Available from: 2010-05-08 Created: 2010-05-07 Last updated: 2017-12-12

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Ljung, Lennart

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