10 citations · 22 across the 5 of their papers we have counts for
5 papers
Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models
Sebastián Espinel-Ríos, Gerrich Behrendt, Jasmin Bauer +6
Optogenetic modulation of adenosine triphosphatase (ATPase) expression represents a novel approach to maximize bioprocess efficiency by leveraging enforced adenosine triphosphate (…
Stochastic Model Predictive Control Utilizing Bayesian Neural Networks
J. Pohlodek, H. Alsmeier, B. Morabito +3
Integrating measurements and historical data can enhance control systems through learning-based techniques, but ensuring performance and safety is challenging. Robust model predict…
Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics
Sebastián Espinel-Ríos, Bruno Morabito, Johannes Pohlodek +3
Biotechnology offers many opportunities for the sustainable manufacturing of valuable products. The toolbox to optimize bioprocesses includes \textit{extracellular} process element…
Machine Learning for Process Control of (Bio)Chemical Processes
Andreas Himmel, Janine Matschek, Rudolph Kok +3
The control of manufacturing processes must satisfy high quality and efficiency requirements while meeting safety requirements. A broad spectrum of monitoring and control strategie…
Flexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC
Johannes Pohlodek, Bruno Morabito, Christian Schlauch +2
Model-based optimization approaches for monitoring and control, such as model predictive control and optimal state and parameter estimation, have been used for decades in many engi…