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bioRxiv · 10.64898/2026.02.07.704591

A Novel Bioprocess Control Strategy Under Uncertainty via Operational Space Identification

Zhu, M.·Pennington, O.·Pincam, T.·Zarei, M.·Kay, S.·Liu, Y.-Q.·Short, M.·Zhang, D.
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Abstract

Bioprocesses are critical for sustainable industrial development but face challenges from their inherent uncertainties that affect efficiency and scalability. This study in-troduces a worst-case operational space design framework, integrating symbolic optimization with scenario-based validation, to preemptively mitigate uncertainties so that key performance indicators are consistently satisfied even under adverse conditions. The methodology is demonstrated through two case studies: a lab-scale fermentation for astaxanthin production and a site-scale anaerobic digestion for biogas production. Process uncertainty is quantified through model parameter variations (2% - 13%) to reflect real-world scenarios. The results indicate that highly flexible operational spaces are identified in both case studies, with control variables able to vary by up to 25% and 15% in the respective systems, while consistently adhering to system constraints. Validation over 10,000 scenarios confirmed 0 violation per case study. The proposed framework delivers validated operational flexibility with modest computational requirements, making it practical for lab-to-site deployment.

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Zhu, M., Pennington, O., Pincam, T., Zarei, M., Kay, S., Liu, Y.-Q., Short, M., Zhang, D.. 2026-02-08. A Novel Bioprocess Control Strategy Under Uncertainty via Operational Space Identification. https://doi.org/10.64898/2026.02.07.704591

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