Modeling and identification of microbial batch fermentation using fuzzy expert system

Abstract

The bioconversion of glycerol to 1,3-Propanediol by Klebsiella pneumoniae (K. pneumoniae) is a complex bioprocess. Because the transport mechanism of glycerol across cell membrane of K. pneumoniae was still not adequately understood, it is difficult to formulate reliable mathematical models. In this study, we aim to explore a novel model for describing the process of glycerol batch fermentation. This is achieved by a hybrid of a fuzzy expert system with a physical model framework. Some important properties of the proposed system are then discussed. To determine the model parameters, we establish a parameter identification model with the relative error of experimental data and simulating results as performance index. An optimization algorithm is developed to solve the identification model on the basis of constrain transcription and smoothing approximation techniques. Finally, the numerical simulations show the validity of the proposed model and the effectiveness of the optimization algorithm.