Alexander Rose M.Sc.
Working area(s)
Learning-supported model predictive control, MPC for embedded systems, Approximate MPC, Monte Carlo methods, Path following and trajectory tracking
Contact
alexander.rose@iat.tu-...
work +49 6151 16-25191
fax +49 6151 16-25172
Work
S3|10 511
Landgraf-Georg-Str. 4
64283
Darmstadt
| Teaching assistant for Modeling, Simulation and Optimization | WS23/24 |
| Teaching assistant for Control of Distributed Cyber-Physical Systems | WS22/23, SS24 |
| Teaching assistant for Modeling and Simulation | SS22, SS23 |
| Topic | Type | Status |
|---|---|---|
| Modellprädiktive Regelung von Quadrocoptern | Bachelor's Thesis | in progress |
| Approximate Model Predictive Trajectory Tracking for an Autonomous Vehicle (opens in new tab) | Master's Thesis | completed |
| Approaches to Multi Agent Systems (opens in new tab) | Proseminar | in progress |
| Tensor Networks for Machine Learning (opens in new tab) | Proseminar | open |
| Explicit Model Predictive Control for Nonlinear Systems (opens in new tab) | Master's Thesis | completed |
| Catching Objects with a Robot Arm (opens in new tab) | Project Course | completed |
| Applications of the Scenario Approach (opens in new tab) | Proseminar | completed |
| Safety Guarantees for a Networked Control System under Delay and Package Loss | Master's Thesis | completed |
| Approximating Model Predictive Controllers using Neural Networks and Gaussian Processes (opens in new tab) | Project Course | completed |
| Personalized Digital Twin of the Human Driver | Master's Thesis | completed |
| Gaussian Processes for Regression and Binary Classification | Proseminar | completed |
| Design of a State Estimator for a Racecar | Bachelor's Thesis | completed |
| Predictive Control of an Inverted Pendulum (opens in new tab) | Project Course | completed |
| Fahrzeugmodell zum Entwurf eines Zustandschätzers | Proseminar | completed |
| Gaussian Process based Model Predictive Control for a PEM Fuel Cell (opens in new tab) | Project Course | completed |
| Machine Learning Methods for System Identification and Control | Master's Thesis | completed |
| Feel free to contact me for further possible topics. Please always attach an overview of your current grades. | ||
| Google Scholar |
| [6] R. Findeisen, A. Rose, K. Graichen and M. Mönnigmann, “Embedded Optimization in Control: An Introduction, Opportunities, and Challenges”, https://doi.org/10.1016/B978-0-443-14081-5.00129-X |
| [5] A. Rose, P. Schaub and R. Findeisen, “Safe and High-Performance Learning of Model Predictive Control using Kernel-Based Interpolation”, accepted, https://arxiv.org/abs/2410.06771 |
| [4] A. Rose, M. Pfefferkorn, H. H. Nguyen and R. Findeisen, “Learning a Gaussian Process Approximation of a Model Predictive Controller with Guarantees,” 2023 62nd IEEE Conference on Decision and Control (CDC), Singapore, Singapore, 2023, pp. 4094-4099, doi: 10.1109/CDC49753.2023.10384047. |
| [3] J. Bethge, M. Pfefferkorn, A. Rose, J. Peters, and R. Findeisen. “Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles” In Proceedings of IFAC World Congress, 2023. accepted. arXiv: https://arxiv.org/abs/2303.04725 |
| [2] L. Kranert, J. Pohlodek, S. Duvigneau, A. Rose, L. Carius, A. Kienle, and R. Findeisen, “Step experiments enable efficient exploration of microbial microaerobic steady states.”, Authorea. February 21, 2023, preprint, doi: 10.22541/au.167700378.88413405/v1. |
| [1] J. Pohlodek, A. Rose, B. Morabito, L. Carius, and R. Findeisen, “Data-driven Metabolic Network Reduction for Multiple Modes Considering Uncertain Measurements,” IFAC-PapersOnLine, vol. 53, no. 2, pp. 16866–16871, 2020, 21st IFAC World Congress, doi: 10.1016/j.ifacol.2020.12.1215 |