Optimization of fed-batch bioreactor using neural network model

Chaudhuri, B and Modak, JM (1998) Optimization of fed-batch bioreactor using neural network model. In: Bioprocess and Biosystems Engineering, 19 (1). pp. 71-79.

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Abstract

An algorithm using feedforward neural network model for determining optimal substrate feeding policies for fed-batch fermentation process is presented in this work. The algorithm involves developing the neural network model of the process using the sampled data. The trained neural network model in turn is used for optimization purposes. The advantages of this technique is that optimization can be achieved without detailed kinetic model of the process and the computation of gradient of objective function with respect to control variables is straightforward. The application of the technique is demonstrated with two examples, namely, production of secreted protein and invertase. The simulation results show that the discrete-time dynamics of fed-batch bioreactor can be satisfactorily approximated using a feedforward sigmoidal neural network. The optimal policies obtained with the neural network model agree reasonably well with the previously reported results.

Item Type:	Journal Article
Publication:	Bioprocess and Biosystems Engineering
Publisher:	Springer-Verlag
Additional Information:	Copyright for this article belongs to Springer-Verlag.
Department/Centre:	Division of Mechanical Sciences > Chemical Engineering
Date Deposited:	28 Dec 2004
Last Modified:	19 Sep 2010 04:15
URI:	http://eprints.iisc.ac.in/id/eprint/1418

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