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Information Technology Journal
  Year: 2008 | Volume: 7 | Issue: 3 | Page No.: 430-439
DOI: 10.3923/itj.2008.430.439
 
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A Radial Basic Function with Multiple Input and Multiple Output Neural Network to Control a Non-Linear Plant of Unknown Dynamics

R. El-Kouatly and G.A. Salman

Abstract:
In this study, the application of the Radial Basis Function (RBF) with Multiple Input and Multiple Output (MIMO) Neural networks to control two types of non linear model plants of unknown dynamics. For the first step a model of a control was developed using the variable liquid-level which can be use in a chemical plant, or power station, where the liquid-level is change within fixed real time. In this control system Radial Basis Function (RBF) neural networks was used to control the liquid-level of the plant. The second step introduced the changes of the liquid-level in real time, also Radial Basis Function with MIMO neural networks has been used to control the level liquid. The study shows that the proposed control system produces accurate results for the two types of models. However, we notice that the training, using back propagation, for the second model take a more considerable time than training the first model.
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How to cite this article:

R. El-Kouatly and G.A. Salman, 2008. A Radial Basic Function with Multiple Input and Multiple Output Neural Network to Control a Non-Linear Plant of Unknown Dynamics. Information Technology Journal, 7: 430-439.

DOI: 10.3923/itj.2008.430.439

URL: https://scialert.net/abstract/?doi=itj.2008.430.439

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