Maik Pfefferkorn

According to our database, Maik Pfefferkorn authored at least 17 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Efficient Controller Learning from Human Preferences and Numerical Data Via Multi-Modal Surrogate Models.

Lukas Theiner, Maik Pfefferkorn, Yongpeng Zhao, Sebastian Hirt, Rolf Findeisen

CoRR, March, 2026

2025

High-Dimensional Surrogate Modeling for Closed-Loop Learning of Neural-Network-Parameterized Model Predictive Control.

Sebastian Hirt, Valentinus Suwanto, Hendrik Alsmeier, Maik Pfefferkorn, Rolf Findeisen

CoRR, December, 2025

Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment.

Yongpeng Zhao, Maik Pfefferkorn, Maximilian Templer, Rolf Findeisen

Proceedings of the IEEE Intelligent Vehicles Symposium, 2025

A Hierarchical Surrogate Model for Efficient Multi-Task Parameter Learning in Closed-Loop Control.

Sebastian Hirt, Lukas Theiner, Maik Pfefferkorn, Rolf Findeisen

Proceedings of the 64th IEEE Conference on Decision and Control, 2025

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

Proceedings of the 2025 American Control Conference, 2025

2024

Stability-informed Bayesian Optimization for MPC Cost Function Learning.

Sebastian Hirt, Maik Pfefferkorn, Ali Mesbah, Rolf Findeisen

CoRR, 2024

Learning Energy-Efficient Trajectory Planning for Robotic Manipulators Using Bayesian Optimization.

Philipp Holzmann, Maik Pfefferkorn, Jan Peters, Rolf Findeisen

Proceedings of the European Control Conference, 2024

Probabilistically Input-to-State Stable Stochastic Model Predictive Control.

Maik Pfefferkorn, Rolf Findeisen

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Safe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control.

Sebastian Hirt, Maik Pfefferkorn, Rolf Findeisen

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Regret and Conservatism of Distributionally Robust Constrained Stochastic Model Predictive Control.

Maik Pfefferkorn, Venkatraman Renganathan, Rolf Findeisen

Proceedings of the American Control Conference, 2024

2023

Regret and Conservatism of Constrained Stochastic Model Predictive Control.

Maik Pfefferkorn, Venkatraman Renganathan, Rolf Findeisen

CoRR, 2023

Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles.

Johanna Bethge, Maik Pfefferkorn, Alexander Rose, Jan Peters, Rolf Findeisen

CoRR, 2023

Learning a Gaussian Process Approximation of a Model Predictive Controller with Guarantees.

Alexander Rose, Maik Pfefferkorn, Hoang Hai Nguyen, Rolf Findeisen

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

High-probability stable Gaussian process-supported model predictive control for Lur'e systems.

Hoang Hai Nguyen, Maik Pfefferkorn, Rolf Findeisen

Eur. J. Control, 2022

Learning secure corridors for model predictive path following control of autonomous systems in cluttered environments.

Philipp Holzmann, Janine Matschek, Maik Pfefferkorn, Rolf Findeisen

Proceedings of the European Control Conference, 2022

Exact Multiple-Step Predictions in Gaussian Process-based Model Predictive Control: Observations, Possibilities, and Challenges.

Maik Pfefferkorn, Michael Maiworm, Rolf Findeisen

Proceedings of the American Control Conference, 2022

2020

Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy.

Maik Pfefferkorn, Michael Maiworm, Christian Wagner, F. Stefan Tautz, Rolf Findeisen

Proceedings of the 59th IEEE Conference on Decision and Control, 2020