Manuel Klädtke M.Sc.
Email: manuel.klaedtketu-dortmundde
Room: Maschinenbaugebäude 2, Raum 3xx
Research interests
- explainability in data-driven predictive control
- predictive control for nonlinear systems (convex reformulations for optimal control problems)
Teaching activities
Introduction to Computational Methods (not only) for Engineers (CME)
Advanced Predictive Control (APC)
Regelungstechnik (Übung)
Further information
04 | 2021 - today: Research assistant in the Control and Cyberphysical Systems Group, Department of Mechanical Engineering, TU Dortmund University
06 | 2020 - 03 | 2021: Student Assistant in the Automatic Control Group and at LEA Power Electronics and Electrical Drives, Department of Electrical Engineering, Paderborn University
10 | 2019 – 03 | 2021: Studies of Electrical Engineering (M. Sc. 03 | 2021) at Paderborn University
05 | 2019 - 04 | 2020: Working Student at Phoenix Contact Electronics GmbH, Bad Pyrmont
04 | 2018 - 07 | 2018: Internship at Phoenix Contact Electronics GmbH, Bad Pyrmont
04 | 2017 - 06 | 2017: Student Assistant at LEA Power Electronics and Electrical Drives, Department of Electrical Engineering, Paderborn University
10 | 2015 – 03 | 2019: Studies of Electrical Engineering (B. Sc. 03 | 2019) at Paderborn University
M. Klädtke and M. Schulze Darup, On Data Usage and Predictive Behavior of Data-Driven Predictive Control With 1-Norm Regularization, IEEE Control Systems Letters, vol. 9, pp. 943-948, 2025. DOI: 10.1109/LCSYS.2025.3575436, Preprint: arXiv:2505.22307
M. Klädtke and M. Schulze Darup, Towards explainable data-driven predictive control with regularizations, at - Automatisierungstechnik, vol. 73, no. 6, pp. 365-382, 2025. DOI: 10.1515/auto-2024-0161, Preprint: arXiv:2503.21952
M. Klädtke and M. Schulze Darup, Implicit predictors in regularized data-driven predictive control, IEEE Control Systems Letters, vol. 7, pp. 2479-2484, 2023. DOI: 10.1007/LCSYS.2023.3285104, Preprint: arXiv:2307.10750
M. Klädtke, M. Schulze Darup, and Daniel E. Quevedo, Extending direct data-driven predictive control towards systems with finite control sets, 2024 European Control Conference (ECC), 3345-3350, 2024. DOI: 10.23919/ECC64448.2024, Preprint: arXiv:2404.02727
M. Klädtke and M. Schulze Darup, Towards a unifying framework for data-driven predictive control with quadratic regularization, Extended Abstract presented at the 26th International Symposium on Mathematical Theory of Networks and Systems MTNS 2024. Reprint: arXiv:2404.02721
M. Klädtke and M. Schulze Darup, Convex NMPC reformulations for a special class of nonlinear multi-input systems with application to rank-one bilinear networks, 22nd IFAC World Congress, 3880-3886, 2023. DOI: 10.1016/j.ifacol.2023.10.1321, Preprint: arXiv:2304.08147
M. Klädtke, D. Teichrib, N. Schlüter, and M. Schulze Darup, A deterministic view on explicit data-driven (M)PC, 61st IEEE Conference on Decision and Control (CDC), 499-504, 2022. DOI: 10.1109/CDC51059.2022.9993384, Preprint: arXiv:2206.07025
M. Klädtke, D. Teichrib, N. Schlüter, and M. Schulze Darup, A note on explicit data-driven (M)PC, Extended Abstracts presented at the 25th International Symposium on Mathematical Theory of Networks and Systems MTNS 2022, 767-770, 2022. DOI: 10.15495/EPub_UBT_00006809
M. Klädtke and M. Schulze Darup, Convex reformulations for a special class of nonlinear MPC problems, 2022 European Control Conference (ECC), 761-768, 2022. DOI: 10.23919/ECC55457.2022.9838061, Preprint: arXiv:2206.08617
M. Schulze Darup, M. Klädtke, and M. Mönnigmann, Exact solution to a special class of nonlinear MPC problems, in Proc. of the 7th IFAC Conference on Nonlinear Model Predictive Control (NMPC), 294-299, 2021. DOI: 10.1016/j.ifacol.2021.08.559