Artificial Neural Networks for On-Line Trained Controllers

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F01%3APU21008" target="_blank" >RIV/00216305:26220/01:PU21008 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Artificial Neural Networks for On-Line Trained Controllers
Original language description
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 differencebetween 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 trannsfer 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.
Czech name
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Czech description
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Project
<a href="/en/project/GA102%2F01%2F1485" target="_blank" >GA102/01/1485: Enviroment for development, modelling and application of heterogenous systems</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Advances in Systems Science: Measurement, Circuits and Control
ISBN
960-8052-39-4
Number of pages of the result
6
Pages from-to
189-194
Number of pages of the book
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Publisher name
Published by WSES Press, http://www.worldses.org
Place of publication
http://www.worldses.org
UT code for WoS chapter
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