Digital Library

of the European Council for Modelling and Simulation



Artificial Neural Networks In Prediction And Predictive Control


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



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.

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