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Performance of Subspace based State-Space System Identification Methods
Chalmers Institute of Technology, Sweden.
Royal Institute of Technology, Sweden.
Royal Institute of Technology, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1993 (English)Report (Other academic)
Abstract [en]

Traditional prediction-error techniques for multivariable system identification require canonical descriptions using a large number of parameters. This problem can be avoided using subspace based methods, since these estimate a state-space model directly from the data. The main computations consist of a QR-decomposition and a singular-value decomposition. Herein, a subspace based technique for identifying general finite-dimensional linear systems is presented and analyzed. The technique applies to general noise covariance structures. Explicit formulas for the asymptotic pole estimation error variances are given. The proposed method is found to perform comparable to a prediction error method in a simple example.

Place, publisher, year, edition, pages
1993.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 1459
Keyword [en]
Linear systems, System identification, Instrumental variable methods
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55586OAI: oai:DiVA.org:liu-55586DiVA: diva2:316332
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2013-07-30

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Ljung, Lennart

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CiteExportLink to record
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  • apa
  • harvard1
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Output format
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