Parameter Identification for Discrete-Time Dynamic Systems by Use of Neural Network and Set-Membership Approaches

Nataliya N. Kussul

doi:10.1615/JAutomatInfScien.v32.i11.50

Journal of Automation and Information Sciences

Editor-in-Chief: Arkadiy A. Chikriy (open in a new tab)

Associate Editors: Vyacheslav F. Gubarev (open in a new tab) Yuriy P. Kondratenko (open in a new tab) Nonna V. Turovyerova (open in a new tab)

Published 12 issues per year

ISSN Print: 1064-2315

ISSN Online: 2163-9337

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Parameter Identification for Discrete-Time Dynamic Systems by Use of Neural Network and Set-Membership Approaches

Volume 32, Issue 11, 2000, pp. 38-44

DOI: 10.1615/JAutomatInfScien.v32.i11.50

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Nataliya N. Kussul
Institute of Space Research of National Academy of Sciences of Ukraine and State Space Agency of Ukraine, Kiev, Ukraine

ABSTRACT

The paper devoted to application of set-membership (ellipsoidal) and neural methods to solution of the parameter identification problem for discrete-time control systems. The comparative analysis of the two algorithms is performed by numerical simulation.

KEY WORDS: discrete-time control systems, ellipsoidal estimates, neural networks, learning algorithm, parameter identification.

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