Use of neural networks for liquid-liquid extraction column modelling: an experimental study

This paper presents a new application of neural networks to the modelling o f a chemical pilot plant: a pulsed liquid-liquid extraction column. This se paration process presents a highly non-linear behaviour and time-varying dy namics. Usually, physical simulation models of chemical plants describing s ome aspects of hydrodynamics and mass transfer are static or very complex a nd need excessive computer time. It is proposed that improved predictions c an be obtained using a multilayer artificial neural network instead of the physical model of the process. The results obtained illustrate the successf ul application of such a neural network modelling approach. (C) 2000 Elsevi er Science S.A. All rights reserved.