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Model reduction of estimated models
Department of Electrical Engineering, Linköping University. (Automatic Control)ORCID iD: 0000-0002-1927-1690
1989 (English)In: Eighth IFAC/IFORS Symposium on Identification and System Parameter Estimation 1988. Part 1, 1989, Vol. 2, no 8, 683-688 p.Conference paper, Published paper (Refereed)
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
1989. Vol. 2, no 8, 683-688 p.
Keyword [en]
Mathematical Statistics - Monte Carlo Methods, Mathematical Techniques - Approximation Theory, Probability, Maximum Likelihood, Model Reduction, Control Systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-55450OAI: oai:DiVA.org:kth-55450DiVA: diva2:471569
Conference
Eighth IFAC/IFORS Symposium on Identification and System Parameter Estimation 1988. Beijing, China. 27 August 1988 - 31 August 1988
Note
QC 20120104. Sponsors: IFAC, Theory Committee; IFAC, Application Committee; IFAC, Education Committee; IFAC, Developing Country Committee; Int Federation of Operational Research Soc (IFORS); et alAvailable from: 2012-01-02 Created: 2012-01-02 Last updated: 2013-09-05Bibliographically approved

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Wahlberg, Bo

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