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Latent State Space Extension for interpretable hybrid mechanistic models
Judit Aizpuru, Maxim Borisyak, Peter Neubauer +1
Mechanistic growth models play a major role in bioprocess engineering, design, and control. Their reasonable predictive power and their high level of interpretability make them an…
Model predictive control and moving horizon estimation for adaptive optimal bolus feeding in high-throughput cultivation of \textit{E. coli}
Jong Woo Kim, Niels Krausch, Judit Aizpuru +4
We discuss the application of a nonlinear model predictive control (MPC) and a moving horizon estimation (MHE) to achieve an optimal operation of \textit{E. coli} fed-batch cultiva…
Fitting nonlinear models to continuous oxygen data with oscillatory signal variations via a loss based on DynamicTime Warping
Judit Aizpuru, Annina Karolin Kemmer, Jong Woo Kim +4
High throughput experimental systems play an important role in bioprocess development, as they provide an efficient way of analysing different experimental conditions and perform s…
Model predictive control guided with optimal experimental design for pulse-based parallel cultivation
Jong Woo Kim, Niels Krausch, Judit Aizpuru +5
Optimal experimental design for parameter precision attempts to maximize the information content in experimental data for a most effective identification of parametric model. With…