Neural network-based NARX models in non-linear adaptive control

• Autorzy: Andrzej Dzieliński
• Języki publikacji: EN

Abstrakty

EN

The applicability of approximate NARX models of non-linear dynamic systems is discussed. The models are obtained by a new version of Fourier analysis-based neural network also described in the paper. This constitutes a reformulation of a known method in a recursive manner, i.e. adapted to account for incoming data on-line. The method allows us to obtain an approximate model of the non-linear system. The estimation of the influence of the modelling error on the discrepancy between the model and real system outputs is given. Possible applications of this approach to the design of BIBO stable closed-loop control are proposed.

Słowa kluczowe

EN

adaptive control; neural networks; nonlinear systems

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2002
• Tom: 12
• Numer: 2
• Strony: 235-240

Daty

wydano

2002

otrzymano

2002-01-21

poprawiono

2002-03-22

Twórcy

autor

Andrzej Dzieliński

• Institute of Control and Industrial Electronics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland

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