10 citations · 21 across the 6 of their papers we have counts for
6 papers · 1 filter
Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging
Sebastian Hirt, Andreas Höhl, Johannes Pohlodek +4
Model predictive control (MPC) is a powerful tool for controlling complex nonlinear systems under constraints, but often struggles with model uncertainties and the design of suitab…
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging
Sebastian Hirt, Andreas Höhl, Joachim Schaeffer +3
Tuning parameters in model predictive control (MPC) presents significant challenges, particularly when there is a notable discrepancy between the controller's predictions and the a…
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…
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…