Economic Nonlinear Model Predictive Control of a U-loop Bioreactor

Tobias Kasper Skovborg Ritschel, Dimitri Boiroux, Marcus Krogh Nielsen, Jakob Kjøbsted Huusom, Sten Bay Jørgensen, John Bagterp Jørgensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


In this paper, we present an algorithm for economic nonlinear model predictive control (NMPC) of singlecell protein production in a U-loop bioreactor. The model of the U-loop bioreactor consists of both stochastic ordinary and partial differential equations. Using a typical finite-volume discretization, the model contains 87 state variables. The NMPC algorithm is based on the continuous-discrete extended Kalman filter and a simultaneous collocation method. We present a closed-loop simulation which demonstrates the computational feasibility of real-time implementation of the NMPC algorithm for startup and steady state operation of the U-loop reactor.
Original languageEnglish
Title of host publicationProceedings of 2020 European Control Conference
Publication date2020
ISBN (Electronic)978-1-7281-8813-3
Publication statusPublished - 2020
Event2020 European Control Conference - Virtual event, Saint Petersburg, Russian Federation
Duration: 12 May 202015 May 2020


Conference2020 European Control Conference
LocationVirtual event
Country/TerritoryRussian Federation
CitySaint Petersburg
Internet address


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