|
|
Digital Library of the
European Council for Modelling and Simulation |
|
Title: |
Artificial
Neural Networks In Prediction And Predictive Control |
|
Authors: |
David Samek, Petr Dostál |
|
Published in:
|
ECMS
2008 Proceedings Edited
by: Loucas S. Louca, Yiorgos Chrysanthou, Zuzana Oplatkova, Khalid Al-Begain ISBN:
978-0-9553018-6-5 Doi: 10.7148/2008 22nd
European Conference on Modelling and Simulation, Nicosia, June
3-6, 2008 |
|
Citation
format: |
Samek, D., & Dostal,
P. (2008). Artificial Neural Networks In Prediction And Predictive Control.
ECMS 2008 Proceedings edited by: L. S. Louca, Y. Chrysanthou, Z. Oplatkova, K. Al-Begain (pp. 525-530).
European Council for Modeling and Simulation. doi:10.7148/2008-0525 |
|
DOI: |
http://dx.doi.org/10.7148/2008-0525 |
|
Abstract: |
In this contribution the three
various artificial neural networks are tested on CATS prediction benchmark.
The results are compared and evaluated. Furthermore, these artificial neural
networks are tested in model predictive control on the t-variant system. The
aim of this paper is to present and compare artificial neural networks as
interesting way how to model and predict nonlinear systems even with
t-variant parameters. The key features of this paper are emphasis of the
computational costs of the selected predictors and usage of adaptive linear network which offers short learning times and remarkable
prediction error. |
|
Full
text: |
|
