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Identification of Composite Local Linear State-Space Models using a Projected Gradient Search
Delft University of Technology, The Netherlands.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Delft University of Technology, The Netherlands.
2002 (English)In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 75, no 16, 1385-1398 p.Article in journal (Refereed) Published
Abstract [en]

An identification method is described to determine a weighted combination of local linear state-space models from input and output data. Normalized radial basis functions are used for the weights, and the system matrices of the local linear models are fully parameterized. By iteratively solving a non-linear optimization problem, the centres and widths of the radial basis functions and the system matrices of the local models are determined. To deal with the non-uniqueness of the fully parameterized state-space system, a projected gradient search algorithm is described. It is pointed out that when the weights depend only on the input, the dynamical gradient calculations in the identification method are stable. When the weights also depend on the output, certain difficulties might arise. The methods are illustrated using serveral examples that have been studied in the literature before.

Place, publisher, year, edition, pages
2002. Vol. 75, no 16, 1385-1398 p.
Keyword [en]
Nonlinear black box model, Local models, Identification, State-space models, Input/output data, Parameterization
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-46857DOI: 10.1080/0020717021000023807OAI: diva2:267753
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2013-07-17

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ReferencesLink to record
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