ABSTRACT
This paper summarizes an industrial necessities and study of the application of neural networks in the area of process monitoring and control. Descriptions of the major activities undertaken in this programmed, which included the application of neural networks for fault detection in a nitrification process and the model based predictive control of a gasoline engine are provided.
The paper also describes some of the practical difficulties that were experienced while applying neural networks and lists the important lessons that were learned through the completion of this project. The main conclusion from the work was that neural networks are capable of improving industrial process monitoring and control systems. However the level of improvement must be analyzed on a problem specific basis and in many applications the use of neural networks is essential.
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