Control of continuous fed-batch fermentation process using neural network based model predictive controller.
Cell growth and metabolite production greatly depend on the feeding of the nutrients in fed-batch fermentations. A strategy for controlling the glucose feed rate in fed-batch baker's yeast fermentation and a novel controller was studied. The difference between the specific carbon dioxide evolution rate and oxygen uptake rate (Qc - Qo) was used as controller variable. The controller evaluated was neural network based model predictive controller and optimizer. The performance of the controller was evaluated by the set point tracking. Results showed good performance of the controller.
Kiran
A Uma Maheshwar
AU
Department of Chemical Engineering, McMaster University, Hamilton, ON L8S 4L7, Canada.
Jana
Asim Kumar
AK
D019149:Bioreactors / Q000382:microbiology / Q000706:statistics & numerical data*; D001709:Biotechnology; D002245:Carbon Dioxide / Q000378:metabolism; D005285:Fermentation; D005947:Glucose / Q000378:metabolism; D008954:Models, Biological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010101:Oxygen Consumption; D012441:Saccharomyces cerevisiae / Q000254:growth & development / Q000378:metabolism
D002245:Carbon Dioxide; D005947:Glucose