most citedState Estimation for Continuous-Discrete-Time Nonlinear Stochastic Systems

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math.OC20231 cited

Dynamic Optimization for Monoclonal Antibody Production

Morten Wahlgreen Kaysfeld, Deepak Kumar, Marcus Krogh Nielsen +1

This paper presents a dynamic optimization numerical case study for Monoclonal Antibody (mAb) production. The fermentation is conducted in a continuous perfusion reactor. We repres…

math.OC2023

Data Assimilation for Combined Parameter and State Estimation in Stochastic Continuous-Discrete Nonlinear Systems

Tarek Diaa-Eldeen, Marcus Krogh Nielsen, Carl Fredrik Berg +2

Data assimilation (DA) provides a general framework for estimation in dynamical systems based on the concepts of Bayesian inference. This constitutes a common basis for the differe…

math.OC2022

Modelling and Economic Optimal Control for a Laboratory-scale Continuous Stirred Tank Reactor for Single-cell Protein Production

Marcus Krogh Nielsen, Jens Dynesen, Jess Dragheim +5

In this paper, we present a novel kinetic growth model for the micro-organism \textit{Methylococcus capsulatus} (Bath) that couples growth and pH. We apply growth kinetics in a mod…

math.OC20221 cited

State Estimation for Continuous-Discrete-Time Nonlinear Stochastic Systems

Marcus Krogh Nielsen, Tobias K. S. Ritschel, Ib Christensen +4

State estimation incorporates the feedback in optimization based advanced process control systems and is very important for the performance of model predictive control. We describe…

math.OC2022

State Estimation Methods for Continuous-Discrete Nonlinear Systems involving Stochastic Differential Equations

Marcus Krogh Nielsen, Tobias K. S. Ritschel, Ib Christensen +4

In this work, we present methods for state estimation in continuous-discrete nonlinear systems involving stochastic differential equations. We present the extended Kalman filter, t…