Digital Twins in Pilot Scale Fermentation: Non-Linear State Estimation for Improving Induction Timing

Mads Stevnsborg, Kurt Selle, Ryan Barton, Oscar A. Prado-Rubio, Carina Gargalo, Krist V. Gernaey, Gary Gilleskie, Jakob K. Huusom*

*Corresponding author for this work

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

Abstract

In this work, a model is developed and implemented for GFPUV production with aerobic fed-batch fermentation of E coli BL21 (DE3). The model parameters are estimated using historical process data and minimizing the prediction and measurement error. The model implements an extended Kalman filter for non-linear state estimation of biomass, glucose, and dissolved oxygen concentration. The filter includes an existing cascade feed-back loop for dissolved oxygen control which improves the predictive accuracy of the filter. The estimator is used during fermentation to predict the induction point based on a threshold glucose concentration which is otherwise determined exclusively with at-line measurements. The validation examples presented in this work show great agreement between the estimated and measured glucose concentrations, making it a useful tool for predicting the time until induction without requiring high-frequency at-line sampling.
Original languageEnglish
Title of host publicationProceedings of the 33rd European Symposium on Computer Aided Process Engineering
EditorsAntonis Kokossis, Michael C. Georgiadis, Efstratios N. Pistikopoulos
Volume52
PublisherElsevier
Publication date2023
Pages2637-2642
ISBN (Print)978-0-443-23553-5, 978-0-443-15274-0
DOIs
Publication statusPublished - 2023
Event33rd European Symposium on Computer Aided Process Engineering - Athens, Greece
Duration: 18 Jun 202321 Jun 2023

Conference

Conference33rd European Symposium on Computer Aided Process Engineering
Country/TerritoryGreece
CityAthens
Period18/06/202321/06/2023
SeriesComputer Aided Chemical Engineering
Volume52
ISSN1570-7946

Keywords

  • Digital Twin
  • Biobased Manufacturing
  • Operator Support
  • Scheduling

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