Model Predictive Control - A Stand out among Competitors for Fed-Batch Fermentation Improvement
Fermentation 2023
Emīls Bolmanis, Konstantīns Dubencovs, Artūrs Šuleiko, Juris Vanags

The fed-batch cultivation is in many ways a benchmark for fermentation processes, and it has been an attractive choice for the biotechnological production of various products in the past decades. The majority of biopharmaceuticals that are presently undergoing clinical trials or are available on the market are manufactured through fed-batch fermentations. A crucial process parameter in fed-batch cultivations is the substrate feed rate, which directly influences the overall process productivity, product quality and process repeatability; henceforth, effective control of this parameter is imperative for a successful fed-batch fermentation process. Two distinct control strategies can be distinguished—open-loop and closed-loop (feedback) control. Each of these methods has its own set of benefits, limitations and suitability for specific bioprocesses. This article surveys and compares the most popular open- and closed-loop methods for substrate feed rate control in fed-batch fermentations. Emphasis is placed on model-predictive feed rate control (MPC)—a stand out among other methods that offers a promising application perspective. The authors also demonstrate a practical example of the implementation of a robust, flexible MPC solution that is suitable for various cultures and runs on standard computer hardware, thus overcoming one of the main reported MPC drawbacks—high computational requirements.


Keywords
fermentation; bioreactors; fed batch; feed rate control; model-based control; PID control; artificial neural network (ANN); fuzzy logic; model predictive control (MPC)
DOI
10.3390/fermentation9030206
Hyperlink
https://www.mdpi.com/2311-5637/9/3/206

Bolmanis, E., Dubencovs, K., Šuleiko, A., Vanags, J. Model Predictive Control - A Stand out among Competitors for Fed-Batch Fermentation Improvement. Fermentation, 2023, Vol. 9, No. 3, Article number 206. ISSN 2311-5637. Pieejams: doi:10.3390/fermentation9030206

Publication language
English (en)
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