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Grey-Box Identification Based on Horizon Estimation and Nonlinear Optimization
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2010 (English)Report (Other academic)
Abstract [en]

In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman filter is included. A procedure how to approximate the bias correction for nonlinear systems is outlined.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. , 9 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2963
Keyword [en]
Grey-box, Identification, Estimation, Nonlinear, Optimization
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-97605ISRN: LiTH-ISY-R-2963OAI: oai:DiVA.org:liu-97605DiVA: diva2:649237
Available from: 2013-09-17 Created: 2013-09-17 Last updated: 2014-08-11Bibliographically approved

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Isaksson, AlfTörnqvist, DavidSjöberg, JohanLjung, Lennart
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • de-DE
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  • en-US
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  • nn-NB
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  • Other locale
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Output format
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