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Journal of Automation and Information Sciences
SJR: 0.238 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimer: 1064-2315
ISSN En ligne: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v43.i6.10
pages 1-15

On the Structural and Parametric Identification under the Limited Uncertainty and Approximating Models of Multidimensional Systems

Vyacheslav F. Gubarev
Institute of Space Research of National Academy of Sciences of Ukraine and State Space Agency of Ukraine, Kiev, Ukraine
Alexey V. Gummel
Institute for Applied Systems Analysis of National Technical University of Ukraine "Kiev Polytechnic Institute", Kiev
Artem A. Kryshtal
Institute for Applied Systems Analysis of National Technical University of Ukraine "Kiev Polytechnic Institute", Kiev
Vladislav Yu. Oles
Institute for Applied Systems Analysis of National Technical University of Ukraine "Kiev Polytechnic Institute", Kiev

RÉSUMÉ

The possibility of spread, through appropriate modifications, of the well-known methods of the stochastic identification to multidimensional systems generating the data, which contain a limited uncertainty, was investigated. It is shown that, in general, only an approximating model of the reduced order with the biased estimates of its parameters can be restored correctly. For systems with different structural properties and signal-to-noise ratio it is found how the parameters of the truncated model coordinate with the dynamic characteristics of the investigated object.


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