Model Based Predictive Control Using Neural Network For Bioreactor Process Control

Abstract

This paper deals with a neural network based GPC structure for a bioprocess control. Comparing to IMC structure, this method offers two advantages: the neural inverting operation of the process model is eliminated and there are various possibilities to adjust the control law properties. The GPC method is applied to a biomass production process and to an enzymatic production process (lipase producing). In both cases many simulation results are presented which illustrate the validity of the method.