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PIVOŇKA, P.
Originální název
Artificial Neural Networks for On-Line Trained Controllers
Typ
kapitola v knize
Jazyk
angličtina
Originální abstrakt
This paper deals with the use of artificial neural networks employed as an on-line trained controller for a real process and simulation model control. Well-known back-propagation method is used as a learning algorithm intended to minimize the difference between the plant’s actual response and the desired reference signal. The influence of neural network’s parameters on a controlled plant output is discussed. We also attempted to find the rules of these parameters adjustment in view of the type of a transfer function in Laplace transform and tested the robustness of our controller burdened with the error signal. Some simulation and real process control results are also presented to evaluate the proposed design. Discussed in the last chapter are the possibilities of creating an adaptive neural controller.
Klíčová slova
back-propagation, artificial neural nets, neural controller, adaptive neural controller
Autoři
Rok RIV
2001
Vydáno
7. 7. 2001
Nakladatel
Published by WSES Press, http://www.worldses.org
Místo
http://www.worldses.org
ISBN
960-8052-39-4
Kniha
Advances in Systems Science: Measurement, Circuits and Control
Edice
Electrical and Computer Engineering Series - A series of Reference Books and Textbooks
Číslo edice
1
Strany od
189
Strany do
194
Strany počet
6
BibTex
@inbook{BUT55021, author="Petr {Pivoňka}", title="Artificial Neural Networks for On-Line Trained Controllers", booktitle="Advances in Systems Science: Measurement, Circuits and Control", year="2001", publisher="Published by WSES Press, http://www.worldses.org", address="http://www.worldses.org", series="Electrical and Computer Engineering Series - A series of Reference Books and Textbooks", edition="1", pages="6", isbn="960-8052-39-4" }