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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)In: Proceedings of the 15th IFAC Symposium on System Identification, 2009, 1175-1180 p.Conference paper, Published paper (Refereed)
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
2009. 1175-1180 p.
Keyword [en]
Continuous time system estimation, Maximum likelihood methods, Toolboxes
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-89073DOI: 10.3182/20090706-3-FR-2004.00195ISBN: 978-3-902661-47-0 (print)OAI: oai:DiVA.org:liu-89073DiVA: diva2:606625
Conference
15th IFAC Symposium on System Identification, Saint Malo, France, July, 2009
Available from: 2013-02-20 Created: 2013-02-19 Last updated: 2013-07-06

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Ljung, Lennart

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  • apa
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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