Abstract
Artificial Neural Networks (ANN) have traditionally enjoyed considerable attention in process control applications. Thus, the paper is focused on real system control design using neural networks. The point is to show whether neural networks bring better performances to nonlinear process control or not. Artificial Neural Network is nowadays a popular methodology with lots of practical and industrial applications. As introduction, some concrete examples of successful application of ANN can be mentioned, e.g. mathematical modeling of bioprocesses [Montague et al., 1994], [Teixeira et al., 2005], prediction models and control of boilers, furnaces and turbines [Lichota et al., 2010] or industrial ANN control of calcinations processes, or iron ore process [Dwarapudi, et al., 2007]. Specifically in our paper, the aim is to explain and describe usage of neural network in the case of nonlinear reactor furnace control.
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