J. Pohlodek

Flexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC

R. Findeisen, P. Zometa, B. Morabito, 2022, ArXiv.

Optimal control and dynamic modulation of the ATPase gene expression for enforced ATP wasting in batch fermentations

R. Findeisen, S. Klamt, K. Bettenbrock, 2022, IFAC-PapersOnLine.

Efficient and Simple Gaussian Process Supported Stochastic Model Predictive Control for Bioreactors using HILO-MPC

R. Findeisen, S. Espinel‐Ríos, B. Morabito, 2022, IFAC-PapersOnLine.

Model-based State Estimation Based on Hybrid Cybernetic Models

Achim Kienle, Rolf Findeisen, Michael Mangold, 2018 .

Stochastic Model Predictive Control Utilizing Bayesian Neural Networks

R. Findeisen, A. Savchenko, B. Morabito, 2023, American Control Conference.

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics

R. Findeisen, S. Klamt, K. Bettenbrock, 2023, ArXiv.

Towards Risk-aware Machine Learning Supported Model Predictive Control and Open-loop Optimization for Repetitive Processes

Anton Savchenko, Rolf Findeisen, Janine Matschek, 2021, IFAC-PapersOnLine.

Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models

B. Morabito, J. Pohlodek, Sebasti'an Espinel-R'ios, 2024, 2401.08556.