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Experiments with Identification of Continuous Time Models
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2009 (English)Report (Other academic)
Abstract [en]

Identification of time-continuous models from sampled data is a long standing topic of discussion, and many approaches have been suggested. The Maximum Likelihood method is asymptotically and theoretically superior to other methods. However, it may suffer from numerical inaccuracies at fast sampling and it also requires reliable initial parameter values. A number of efficient and useful alternatives to the maximum-likelihood method have been developed over the years. The most important of these are State-Variable filters, combined with Instrumental Variable methods, including the simplified refined IV method. In this contribution we perform unpretentious numerical experiments to comment on these methods, and their mutual benefits.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. , 9 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2907
Keyword [en]
Continuous time system estimation, Maximum likelihood methods, Toolboxes
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56068ISRN: LiTH-ISY-R-2907OAI: oai:DiVA.org:liu-56068DiVA: diva2:316868
Projects
CADICS
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-09-03Bibliographically approved

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Ljung, Lennart

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CiteExportLink to record
Permanent link

Direct link
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