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Model Reduction of Estimated Models
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1988 (English)Report (Other academic)
Abstract [en]

This paper deals with the connection between system identification and model reduction. We will from a statistical point of view discuss how to reduce the order of high-order models obtained from an identification experiment. We will apply these results to estimate transfer functions by means of a high-order FIR model and model reduction. The model reduction techniques considered are: Frequency weighted L2-norm model reduction and model reduction via a truncated frequency weighted balanced realization.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1988. , 6 p.
LiTH-ISY-I, ISSN 8765-4321 ; 906
Keyword [en]
Mathematical statistics, Monte Carlo methods, Approximation theory, Maximum likelihood, Control systems
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-104209OAI: diva2:695361
Available from: 2014-02-10 Created: 2014-02-10 Last updated: 2014-02-10

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Automatic ControlThe Institute of Technology
Control Engineering

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ReferencesLink to record
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