Bioprocess hybrid parametric/nonparametric modelling based on the concept of mixture of experts

This paper presents a novel method for bioprocess hybrid parametric/nonparametric modelling based on mixture of experts (ME) and the Expectation Maximisation (EM) algorithm. The bioreactor system is described by material balance equations whereas the cell population subsystem is described by an adjustable mixture of parametric/nonparametric sub-models inspired in the ME architecture. This idea was motivated by the fact that cellular metabolism has an inherent "modular" structure, organised in metabolic reactions pathways, with complex interactions. As main conclusions it can be stated that MEs trained with the EM algorithm are able to systematically detect metabolic shifts with the individual experts developing expertise in describing the individual pathways. The MLP and the ME outperform systematically the RBF network in terms of the ratio model accuracy/number of parameters. The ME network outperforms the MLP network in its ability to describe metabolic switches.