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Local Modelling with A Priori Known Bounds Using Direct Weight Optimization
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Institute of Control Sciences, Russia.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2003 (English)Report (Other academic)
Abstract [en]

In local modelling, function estimates are computed from observations in a local neighborhood of the point of interest. A central question is how to choose the size of the neighborhood. Often this question has been tackled using asymptotic (in the number of observations) arguments. The recently introduced direct weight optimization approach is a non-asymptotic approach, minimizing an upper bound on the mean squared error. In this paper the approach is extended to also take a priori known bounds on the function and its derivative into account. It is shown that the result will sometimes, but not always, be improved by this information. The proposed approach can be applied, e.g., to prediction of nonlinear dynamic systems and model predictive control.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2003. , 12 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2484
Keyword [en]
Local modelling, non-parametric identication, nonlinear systems, minimax techniques, convex programming
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55904ISRN: LiTH-ISY-R-2484OAI: oai:DiVA.org:liu-55904DiVA: diva2:316629
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-03Bibliographically approved

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Roll, JacobLjung, Lennart

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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