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Subspace Identification of Continuous-Time Models Using Generalized Orthonormal Bases
Beijing Inst Technol, Peoples R China.
Beijing Inst Technol, Peoples R China.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
Delft Univ Technol, Netherlands.
2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

The continuous-time subspace identification using state-variable filtering has been investigated for a long time. Due to the simple orthogonal basis functions that were adopted by the existing methods, the identification performance is quite sensitive to the selection of the system-dynamic parameter associated with an orthogonal basis. To cope with this problem, a subspace identification method using generalized orthonormal(Takenaka-Malmquist) basis functions is developed, which has the potential to perform better than the existing state-variable filtering methods since the adopted Takenaka-Malmquist basis has more degree of freedom in selecting the system-dynamic parameters. As a price for the flexibility of the generalized orthonormal bases, the transformed state-space model is time-varying or parameter-varying which cannot be identified using traditional subspace identification methods. To this end, a new subspace identification algorithm is developed by exploiting the structural properties of the time-variant system matrices, which is then validated by numerical simulations.

Place, publisher, year, edition, pages
IEEE , 2017.
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-145491DOI: 10.1109/CDC.2017.8264440ISI: 000424696905011ISBN: 978-1-5090-2873-3 OAI: oai:DiVA.org:liu-145491DiVA, id: diva2:1187184
Conference
IEEE 56th Annual Conference on Decision and Control (CDC)
Note

Funding Agencies|National Research Funding of China [61720106011]; European Research Council under the European Unions Seventh Framework Programme (FP7) / ERC grant [339681]

Available from: 2018-03-02 Created: 2018-03-02 Last updated: 2018-03-02

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf