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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Elman Neural Networks In Model Predictive Control |
Authors: |
David Samek |
Published in: |
(2009).ECMS
2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel
Pedrera. European Council for Modeling and
Simulation. doi:10.7148/2009 ISBN: 978-0-9553018-8-9 23rd
European Conference on Modelling and Simulation, Madrid, June
9-12, 2009 |
Citation
format: |
Samek, D. (2009). Elman Neural Networks
In Model Predictive Control. ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L.
Montes, L. M. Doncel Pedrera (pp. 577-581). European Council for
Modeling and Simulation. doi:10.7148/2009-0577-0581 |
DOI: |
http://dx.doi.org/10.7148/2009-0577-0581 |
Abstract: |
The goal of this paper is to
present interesting way how to model and predict nonlinear systems using
recurrent neural network. This type of artificial neural networks is
underestimated and marginalized. Nevertheless, it offers superior modelling features at reasonable computational costs.
This contribution is focused on Elman Neural Network, two-layered recurrent
neural network. The abilities of this network are presented in the nonlinear
system control. The task of the controller is to control the liquid level in
the second of two interconnected cylindrical tanks. The mathematical model of
the real- time system was derived in order to test predictor and consequently
the controller in Matlab/Simulink simulations. |
Full
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