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Logo of the Control and Cyberphysical Systems Group
Department of Mechanical Engineering
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Research Assistant

Dieter Teichrib M.Sc.

Email: dieter.teichribtu-dortmundde

Tel.: +49 231 / 755 - 5619

Room: Maschinenbaugebäude 2, Raum 317

Office hours: on request

© RCS​/​DT

Research interests

  • machine learning for control  (tailored topologies of artificial neural networks for learning-based control)
  • optimal and robust control (linear/explicit/robust MPC, time-optimal control)

Teaching activities

Regelungstechnik (Übung)

Angewandte konvexe Optimierung (Übung)

all courses

Further information

01 | 2021 - today: Research assistant in the Control and Cyberphysical Systems Group, Department of Mechanical Engineering, TU Dort­mund University

01 | 2019 - 12 | 2020: Studies on Electrical Engineering (M.Sc. 12 | 2020) at the Paderborn University

06 | 2019 - 09 | 2020: Scientific assistant in the Automatic Control Group, Department of Electrical Engineering, Paderborn University

07 | 2019 - 10 | 2019: Scholarship Deutschlandstipendium

10 | 2015 - 01 | 2019: Studies on Electrical Engineering (B.Sc. 01 | 2019) at the Paderborn University

01 | 2018 - 10 | 2018: Student assistant in the Signal and System Theory Group, Department of Electrical Engineering, Paderborn University

09 | 2011 - 07 | 2014: Vocational training as an Industrial Electronics Technician at the Siemens AG in Bielefeld

[C] D. Teichrib and M. Schulze Darup. Piecewise regression via mixed-integer programming for MPC, Proc. of the 6th Annual Learning for Dynamics & Control Conference, pp. 337-348, 2024, available at: https://proceedings.mlr.press/v242/teichrib24a.html

[C] D. Teichrib and M. Schulze Darup. Reachability analysis for piecewise affine systems with neural network-based controllers, 63rd IEEE Conference on Decision and Control (CDC), 2024 (accepted). Preprint: https://arxiv.org/abs/2411.03834

D. Teichrib and M. Schulze Darup, Efficient Computation of Lipschitz Constants for MPC with Symmetries, Proc. of the 62nd IEEE Conference on Decision and Control (CDC), pp. 6685-6691, 2023. DOI: 10.1109/CDC49753.2023.10383472. Preprint: arXiv:2311.04580.

D. Teichrib and M. Schulze Darup, Error bounds for maxout neural network approximations of model predictive control, IFAC-PapersOnLine, 56(2): pp. 10113-10119, 2023. DOI: 10.1016/j.ifacol.2023.10.883. Preprint: arXiv:2304.08779.

H. Nikbakht and M. T. Khoshmehr, B. van Someren, D. Teichrib, M. Hammer, J. Förstner, B. I. Akca. Asymmetric, non-uniform 3-dB directional coupler with 300-nm bandwidth and a small footprint, Optics Letters, 48(2): pp. 207-210, 2023. DOI: 10.1364/OL.476537

D. Teichrib and M. Schulze Darup, Tailored max-out networks for learning convex PWQ functions, 2022 European Control Conference (ECC), 2022. DOI: 10.23919/ECC55457.2022.9838225, Seiten: 2272-2278. Preprint: arXiv.2206.06826.

D. Teichrib and M. Schulze Darup, Tailored neural networks for learning optimal value functions in MPC, 60th IEEE Conference on Decision and Control (CDC), 2021. DOI: 10.1109/CDC45484.2021.9683528, Seiten: 5281-5287. Preprint: arXiv:2112.03975.

M. Schulze Darup and D. Teichrib, Efficient computation of RPI sets for tube-based robust mpc, Proc. of the 2019 European Control Conference (ECC), pp. 325-330, 2019. DOI: 10.23919/ECC.2019.8796265

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