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ŠVANCARA, K., PIVOŇKA, P.
Originální název
Closed Loop On-Line Identification Based on Neural Networks in Adaptive Optimal Controller
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Last ten years, algorithms based on Neural Networks were used successfully for the pattern recognition, process control and system identification. Artificial Neural Networks applied this way have been strongly developing together with the classical control. It is mainly because of their self-learning property and wide-range of easy algorithm designs. Using Neural Networks for identification is well-known strategy where the process is observed usually through its input and output only. The real process is often influenced by disturbances. In this case, the more identified transfer function is inaccurate the more as disturbance influences IO of the measured process. This paper shows a comparison between on-line identification (in the real time) based on Neural Networks and a classical identification implemented in adaptive optimal controller. The setting of the sampling period for the both identification methods is investigated.
Klíčová slova
On-Line neural identification, optimal adaptive controller,ARMA model, LD-FIL
Autoři
Rok RIV
2002
Vydáno
4. 9. 2002
Nakladatel
Rektor der Hochschule Zittau/Görlitz
Místo
Zittau, Německo
ISBN
3-9808089-2-0
Kniha
Proceedings East West Fuzzy Colloquium 2002
Strany od
218
Strany do
223
Strany počet
6
BibTex
@inproceedings{BUT4918, author="Kamil {Švancara} and Petr {Pivoňka}", title="Closed Loop On-Line Identification Based on Neural Networks in Adaptive Optimal Controller", booktitle="Proceedings East West Fuzzy Colloquium 2002", year="2002", pages="6", publisher="Rektor der Hochschule Zittau/Görlitz", address="Zittau, Německo", isbn="3-9808089-2-0" }