Flexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC. - Johannes Pohlodek; Bruno Morabito; Christian Schlauch; Pablo Zometa; Rolf Findeisen (CoRR, 2022)

Stochastic Model Predictive Control Utilizing Bayesian Neural Networks. - Johannes Pohlodek; Hendrik Alsmeier; Bruno Morabito; Christian Schlauch; Anton Savchenko; Rolf Findeisen (ACC, 2023)

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics. - Sebastián Espinel-Ríos; Bruno Morabito; Johannes Pohlodek; Katja Bettenbrock; Steffen Klamt; Rolf Findeisen (CoRR, 2023)

Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models. - Sebastián Espinel-Ríos; Gerrich Behrendt; Jasmin Bauer; Bruno Morabito; Johannes Pohlodek; Andrea Schütze; Rolf Findeisen; Katja Bettenbrock; Steffen Klamt (CoRR, 2024)

Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging. - Sebastian Hirt; Andreas Höhl; Joachim Schaeffer; Johannes Pohlodek; Richard D. Braatz; Rolf Findeisen (CoRR, 2024)

Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging. - Sebastian Hirt; Andreas Höhl; Johannes Pohlodek; Joachim Schaeffer; Maik Pfefferkorn; Richard D. Braatz; Rolf Findeisen (CoRR, 2024)