NEUROIDENTIFICATION OF A BIOTECHNOLOGICAL PROCESS - ISSUES AND APPLICATION

Fermentations are highly non-linear time-varying and inaccurately mode lled processes. Our work towards the generation of a neural network mo del of an industrial secondary metabolic fermentation process is prese nted in this paper. The construction methodology and the various issue s arising during the design, training and testing stages are also disc ussed. Such issues addressed in this paper include the treatment of dy namics and the determination of the number of hidden nodes. The useful ness of the neural network model with regard to the on-line estimation of fundamental measurements is demonstrated and its part in a control system is highlighted.