Linearisation of process models : an analysis and applications using neural networks

Abstract

The emergence of Artificial Neural Networks (ANNs) has rekindled interest in nonlinear control theory. Some applications of Artificial Neural Networks to process control have been reported in the literature. The capability of ANN is that even with an inappropriate choice of input variables, ANN can be trained in such a way that many of the input variables may have little effect on the output. In such cases, the importance of knowledge of the process to be modelled cannot be overemphasised. A good understanding of the nature of the nonlinearity of process is important for proper application and exploitation of ANN for modelling and control.