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A Subspace Based Instrumental Variable Method for State-Space System Identification
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0003-2298-6774
Chalmers University of Technology, Department of Applied Electronics, S-412 96 Gothenburg, Sweden.
1994 (English)In: Proceedings of 10th IFAC Symposium on System Identification, 1994, 139-144 p.Conference paper (Refereed)
Abstract [en]

Traditional prediction-error techniques for multivariable system identification require canonical descriptions using a large number of parameters. This problem may be avoided using subspace based methods, since these estimate a state-space model directly from the data. In this paper, a subspace based technique for identifying general finite-dimensional linear systems is presented and analyzed. Similar to subspace based identification schemes, the space spanned by the extended observability matrix is first estimated. The system parameters are then extracted by reparametrizing the nullspace of the subspace estimate in terms of the coefficients of the characteristic polynomial. A quadratic problem is obtain and based on a statistical analysis, an optimal weighting derived.

Place, publisher, year, edition, pages
1994. 139-144 p.
Keyword [en]
System identification; multivariable systems; parameter estimation; instrumental variable method
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-92599OAI: diva2:513875
10th IFAC Symposium on System Identification, Copenhagen, Denmark
NR 20140805Available from: 2012-04-03 Created: 2012-04-03 Last updated: 2012-04-03Bibliographically approved

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