Control of continuous fed-batch fermentation process using neural network based model predictive controller

2009 ◽  
Vol 32 (6) ◽  
pp. 801-808 ◽  
Author(s):  
A. Uma Maheshwar Kiran ◽  
Asim Kumar Jana
Keyword(s):  
Neural Network ◽  
Batch Fermentation ◽  
Fermentation Process ◽  
Fed Batch ◽  
Model Predictive Controller ◽  
Fed Batch Fermentation ◽  
Predictive Controller

A Recurrent Neural Network Model of the B.t. Fed-Batch Fermentation Process 1

2001 ◽  
Vol 34 (5) ◽  
pp. 385-390
Author(s):  
Barrera-Cortés J. ◽  
Baruch I. ◽  
Valdez-Castro L. ◽  
Vázquez-Cervantes V.
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Recurrent Neural Network ◽  
Neural Network Model ◽  
Batch Fermentation ◽  
Fermentation Process ◽  
Fed Batch ◽  
Fed Batch Fermentation

scholarly journals Modelling of ergosterol production by S. cerevisiae in presence of n-dodecane as oxygen-vector

2021 ◽  
Vol 26 (2) ◽  
pp. 2464-2470
Author(s):  
ANCA-IRINA GALACTION ◽  
◽  
ALEXANDRA CRISTINA BLAGA ◽  
ALEXANDRA TUCALIUC ◽  
LENUŢA KLOETZER ◽  
...  
Keyword(s):  
Batch Fermentation ◽  
Fermentation Process ◽  
Biomass Concentration ◽  
Aeration Rate ◽  
Yeast Cells ◽  
Fed Batch ◽  
Volumetric Fraction ◽  
Fed Batch Fermentation ◽  
Oxygen Vector ◽  
Efficient Fermentation

The previous studies on ergosterol production by Saccharomyces cerevisiae in presence of n-dodecane as oxygen-vector have been continued by mathematical modelling the fermentation process. In this purpose, the most efficient fermentation regime has been considered, namely fed-batch fermentation, and was based on the influences of hydrocarbon volumetric fraction, biomass concentration, and aeration rate on the ergosterol content inside the yeast cells. The model describing the fermentation process has been established by means of the statistical analysis, using a factorial experiment of second order. The considered variables control the ergosterol production in a 94.4% extent, the biomass concentration exhibiting the most important influence.

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