Hybrid modelling of fermentation processes: a study on the use of modular neural networks for modelling cells reaction kinetics

Hybrid models of fermentation processes usually employ Artificial Neural Networks (ANNs) for modelling cells reaction kinetics. The most employed network types are the Multi Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. The main objective in this work was to investigate the applicability of modular neural networks for modelling cell reaction kinetics in bioreactors. The study was supported with simulations of a wastewater treatment process using the ASM model number 2d. The main results show that modular networks if trained with the expectation maximisation algorithm are able to discriminate between pathways and to develop expertise in describing the different pathways. However no advantage was observed in terms of the ratio modelling accuracy/number of parameters.