Artificial Neural Network with Radial Basis Function in Model Predictive Control

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28110%2F09%3A63508098" target="_blank" >RIV/70883521:28110/09:63508098 - 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 Network with Radial Basis Function in Model Predictive Control
Original language description
This paper deals with application of artificial neural network with radial basis function as a predictor in model predictive control. Radial basis function neural networks are known for their fast training. Thus, this type of artificial neural networks offers promising way how to reduce computational cost during offline predictor training and eventual online adaptation. The features of this type of artificial neural network are presented in simulations in MATLAB/Simulink on the nonlinear system control.The aim of this paper is to suggest one approach how to solve nonlinear prediction problem using artificial neural network respecting computational demands of the predictor.
Czech name
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Czech description
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Project
<a href="/en/project/GP102%2F07%2FP137" target="_blank" >GP102/07/P137: Predictive control using artificial neural networks with online adaptation of predictor</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 10th International Carpathian Control Conference ICCC 2009
ISBN
83-89772-51-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
AGH University of Science and Technology
Place of publication
Krakow
Event location
Zakopane
Event date
May 24, 2009
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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