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A modular approach to constraint satisfaction under uncertainty - with application to bioproduction systems
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). AdBIOPRO, Competence Ctr Adv Bioprod Continuous Proc, Stockholm, Sweden..ORCID iD: 0000-0002-6182-9299
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). AdBIOPRO, Competence Ctr Adv Bioprod Continuous Proc, Stockholm, Sweden..ORCID iD: 0000-0001-8251-9006
2022 (English)In: IFAC PAPERSONLINE, Elsevier BV , 2022, Vol. 55, no 7, p. 592-599Conference paper, Published paper (Refereed)
Abstract [en]

The paper proposes a modular-based approach to constraint handling in process optimization and control. This is partly motivated by the recent interest in learning-based methods, e.g., within bioproduction, for which constraint handling under uncertainty is a challenge. The proposed constraint handler, called predictive filter, is combined with an adaptive constraint margin to minimize the cost of violating soft constraints due to uncertainty and disturbances. The module can be combined with any controller and is based on modifying the controller output, in a least squares sense, such that constraints are satisfied within the considered horizon. The proposed method is computationally efficient and suitable for real-time applications. The effectiveness of the method is illustrated by a simple heater example and a nonlinear and time-varying example in penicillin fed-batch production optimization. Copyright

Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 55, no 7, p. 592-599
Keywords [en]
Constraint handling, predictive filter, adaptive constraint margin, bioproduction
National Category
Subatomic Physics Probability Theory and Statistics Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-318244DOI: 10.1016/j.ifacol.2022.07.508ISI: 000841442800012Scopus ID: 2-s2.0-85137058747OAI: oai:DiVA.org:kth-318244DiVA, id: diva2:1697201
Conference
13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS), JUN 14-17, 2022, Busan, SOUTH KOREA
Note

QC 20220920

Available from: 2022-09-20 Created: 2022-09-20 Last updated: 2024-04-04Bibliographically approved

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Wang, YuChen, XiaoJacobsen, Elling W.

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CiteExportLink to record
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  • apa
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