Surrogate Modeling for Control of Microbial Biopolymer Production Process
Dürr R, Otto E, Kok RL, Duvigneau S, Kienle A, Bück A (2025)
Publication Type: Conference contribution
Publication year: 2025
Journal
Publisher: Elsevier B.V.
Book Volume: 59
Pages Range: 169-174
Conference Proceedings Title: IFAC-PapersOnLine
Event location: Vienna, AUT
DOI: 10.1016/j.ifacol.2025.03.030
Abstract
In this contribution, the Dynamic Mode Decomposition with control (DMDc) is used to derive a surrogate model of a continuous PHA biopolymer production process based on a recently published complex process model. Here, snapshot simulation data of the original model is processed to obtain a linear surrogate model formulation using delay coordinates. The quality of the surrogate is statistically validated within simulation studies. Additionally, the influence of the of the order of delay coordinates is investigated. It is shown, that the highly nonlinear dynamics of the PHA-manufacturing process can be approximated accurately by the DMD-based model even for large variations of initial conditions and control variables. This offers the opportunity to apply well-studied and established tools from robust and optimal control in future investigations.
Authors with CRIS profile
Involved external institutions
Hochschule Magdeburg-Stendal
Germany (DE)
Otto-von-Guericke-Universität Magdeburg
Germany (DE)
Max-Planck-Institut für Dynamik komplexer technischer Systeme / Max Planck Institute for Dynamics of Complex Technical Systems
Germany (DE)
Germany (DE)
Otto-von-Guericke-Universität Magdeburg
Germany (DE)
Max-Planck-Institut für Dynamik komplexer technischer Systeme / Max Planck Institute for Dynamics of Complex Technical Systems
Germany (DE)
How to cite
APA:
Dürr, R., Otto, E., Kok, R.L., Duvigneau, S., Kienle, A., & Bück, A. (2025). Surrogate Modeling for Control of Microbial Biopolymer Production Process. In Lukasz Jadachowski (Eds.), IFAC-PapersOnLine (pp. 169-174). Vienna, AUT, AT: Elsevier B.V..
MLA:
Dürr, Robert, et al. "Surrogate Modeling for Control of Microbial Biopolymer Production Process." Proceedings of the 11th Vienna International Conference on Mathematical Modelling, MATHMOD 2025, Vienna, AUT Ed. Lukasz Jadachowski, Elsevier B.V., 2025. 169-174.
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