Neural network process control

Abstract

Neural Networks are increasingly finding engineering applications. Most early applications were in the areas of pattern recognition and modeling. This paper shows how neural network models can be used in process control. Two separate techniques are illustrated, each with a specific example application. One involves using the network itself as the inverse model, by fixing the neural network weights and training on the inputs to give the desired output pattern. The other suggests using the pattern recognition ability of a neural network to identify an appropriate lower order linear model to use for controller design.