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Maximizing batch fermentation efficiency by constrained model-based optimization and predictive control of adenosine triphosphate turnover

Espinel-Ríos, Sebastián ; Bettenbrock, Katja ; Klamt, Steffen ; Findeisen, Rolf (2022)
Maximizing batch fermentation efficiency by constrained model-based optimization and predictive control of adenosine triphosphate turnover.
In: AIChE Journal, 68 (4)
doi: 10.1002/aic.17555
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

We present a constrained model-based optimization and predictive control framework to maximize the production efficiency of batch fermentations based on the core idea of manipulating adenosine triphosphate (ATP) wasting. In many bioprocesses, enforced ATP wasting —rerouting ATP use towards an energetically possibly suboptimal path— allows increasing the metabolic flux towards the product, thereby enhancing product yields and specific productivities. However, this often comes at the expense of lower biomass yields and reduced volumetric productivities. To maximize the overall efficiency, we formulate ATP wasting as a model-based optimal control problem. This allows for balancing trade-offs between different objectives such as product yield and volumetric productivity for batch fermentations. Unlike static metabolic control, one obtains a higher degree of flexibility, adaptability, and competitiveness. This can be advantageous towards achieving a sustainable and economically efficient biotechnology industry. To compensate for model-plant mismatch, disturbances, and uncertainties, we propose not only solving the optimal control problem once. Instead, we exploit the concept of moving horizon model predictive control combined with constraint-based dynamic modeling to capture the fermentation dynamics. The approach is underlined considering the industrially relevant bioproduction of lactate by Escherichia coli. We discuss practical challenges for the described control strategy and provide an outlook towards future developments.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Espinel-Ríos, Sebastián ; Bettenbrock, Katja ; Klamt, Steffen ; Findeisen, Rolf
Art des Eintrags: Bibliographie
Titel: Maximizing batch fermentation efficiency by constrained model-based optimization and predictive control of adenosine triphosphate turnover
Sprache: Englisch
Publikationsjahr: April 2022
Verlag: Wiley Periodicals LLC
Titel der Zeitschrift, Zeitung oder Schriftenreihe: AIChE Journal
Jahrgang/Volume einer Zeitschrift: 68
(Heft-)Nummer: 4
DOI: 10.1002/aic.17555
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Kurzbeschreibung (Abstract):

We present a constrained model-based optimization and predictive control framework to maximize the production efficiency of batch fermentations based on the core idea of manipulating adenosine triphosphate (ATP) wasting. In many bioprocesses, enforced ATP wasting —rerouting ATP use towards an energetically possibly suboptimal path— allows increasing the metabolic flux towards the product, thereby enhancing product yields and specific productivities. However, this often comes at the expense of lower biomass yields and reduced volumetric productivities. To maximize the overall efficiency, we formulate ATP wasting as a model-based optimal control problem. This allows for balancing trade-offs between different objectives such as product yield and volumetric productivity for batch fermentations. Unlike static metabolic control, one obtains a higher degree of flexibility, adaptability, and competitiveness. This can be advantageous towards achieving a sustainable and economically efficient biotechnology industry. To compensate for model-plant mismatch, disturbances, and uncertainties, we propose not only solving the optimal control problem once. Instead, we exploit the concept of moving horizon model predictive control combined with constraint-based dynamic modeling to capture the fermentation dynamics. The approach is underlined considering the industrially relevant bioproduction of lactate by Escherichia coli. We discuss practical challenges for the described control strategy and provide an outlook towards future developments.

ID-Nummer: Artikel-ID: e17555
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Erstveröffentlichung

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Control and Cyber-Physical Systems (CCPS)
Hinterlegungsdatum: 14 Jan 2022 11:53
Letzte Änderung: 22 Jul 2024 13:10
PPN: 490015603
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