@inproceedings{df2addff16df4cf697e3e7af790bd790,
title = "Digital Twins in Pilot Scale Fermentation: Non-Linear State Estimation for Improving Induction Timing",
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.",
keywords = "Digital Twin, Biobased Manufacturing, Operator Support, Scheduling",
author = "Mads Stevnsborg and Kurt Selle and Ryan Barton and Prado-Rubio, {Oscar A.} and Carina Gargalo and Gernaey, {Krist V.} and Gary Gilleskie and Huusom, {Jakob K.}",
year = "2023",
doi = "10.1016/B978-0-443-15274-0.50419-4",
language = "English",
isbn = "978-0-443-23553-5",
volume = "52",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier",
pages = "2637--2642",
editor = "Kokossis, {Antonis } and {C. Georgiadis}, {Michael } and {N. Pistikopoulos}, Efstratios",
booktitle = "Proceedings of the 33rd European Symposium on Computer Aided Process Engineering",
address = "United Kingdom",
note = "33rd European Symposium on Computer Aided Process Engineering, ESCAPE33 ; Conference date: 18-06-2023 Through 21-06-2023",
}