Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study

Real-time estimation of biomass and specific growth rate in physiologically variable recombinant fed-batch processes

The real-time measurement of biomass has been addressed since many years. The quantification of biomass in the induction phase of a recombinant bioprocess is not straight forward, since biological burden, caused by protein expression, can have a significant impact on the cell morphology and physiology. This variability potentially leads to poor generalization of the biomass estimation, hence is...

Fed-batch Cultivation of Recombinant Escherichia coli Producing Human Interferon-γ Under Controlled Specific Growth Rate

Optimal Adaptive Control of Fed-batch Fermentation Processes

This paper presents a unifying methodology for optimization of biotechnological processes, namely optimal adaptive control, which combines the advantages of both the optimal control and the adaptive control approaches. As an example, the design of a substrate feeding rate controller for a class of biotechnologlcal processes in stirred tank reactors characterized by a decoupling between biomass ...

Specific Growth Rate and Sliding Mode Stabilization of Fed-Batch Processes

Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited. Global Journal of Computer Science and Technology Volume 11 Issue 20 Version 1.0 December 2011 Type: Double Blind Peer Reviewed International Research Journal Publisher: Global Journals I...

Self-Organizing Modelling of Biotechnological Batch and Fed-Batch Fermentations

The paper at hand deals with an approach for the automatic generation of dynamic nonlinear process models. These models are obtained from experimental process data as well as from theoretical biological and chemical reeections using the ideas of Genetic Programming for the supervision and coordination of the symbolic model structure during the automatic development.