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Department of Mechanical Engineering
Our research results

Publications

Below, you find all publications of the group since its (re)formation in 2020. Some earlier publications can be found in the profiles of the team members.

The publications are sorted by year and their types are indicated by prefixes. In this context, [J] stands for journal papers, [B] for books or book chapters, [C] for conference papers, [A] for (extented) conference abstracts, and [T] for (Ph.D.) theses.

List of publications

[C] J. Adamek, N.Schlüter and M. Schulze Darup. On the design of stabilizing FIR controllers, 2023 (accepted).

[C] D. Teichrib and M. Schulze Darup. Piecewise regression via mixed-integer programming for MPC, 6th Annual Learning for Dynamics & Control Conference (L4DC), 2024 (accepted).

[A] M. Klädtke and M. Schulze Darup. Towards Explainable Data-Driven Predictive Control with Regularizations, 2024er Sitzung des GMA-Fachausschuss 2.15, Schloss Reisensburg, 2024.

[A] D. Teichrib and M. Schulze Darup. Analysis of Neural Network-Based Controllers via Mixed-Integer Programming, 2024er Sitzung des GMA-Fachausschuss 2.15, Schloss Reisensburg, 2024.

 

[J] N. Schlüter, P. Binfet and M. Schulze Darup. A brief survey on encrypted control: From the first to the second generation and beyond, Annual Reviews in Control, 2023. DOI: 10.1016/j.arcontrol.2023.100913

[J] P. Binfet, J. Adamek, N. Schlüter and M. Schulze Darup. Towards privacy-preserving cooperative control via encrypted distributed optimization, at - Automatisierungstechnik, vol. 71, no. 9, pp. 736-747, 2023. DOI: 10.1515/auto-2023-0082

[J] 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, Reprint:
arXiv:2307.10750

[C] D. Teichrib and M. Schulze Darup. Efficient computation of Lipschitz constants for MPC with symmetries, 62nd IEEE Conference on Decision and Control (CDC), 2023. Preprint:
arXiv.2311.04580

[C] P. Binfet, N.Schlüter and M. Schulze Darup. On the security of randomly transformed quadratic programs related to privacy-preserving cloud-based control, 62nd IEEE Conference on Decision and Control (CDC), 2023. Preprint: arXiv.2311.05215

[C] 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, 2023. DOI: 10.1016/j.ifacol.2023.10.1321, Preprint: arXiv.2304.08147

[C] P. Binfet, N. Schlüter, and M. Schulze Darup. Cryptanalysis of Random Affine Transformations for Encrypted Control, 22nd IFAC World Congress, pp. 11209-11216, 2023. DOI: 10.1016/j.ifacol.2023.10.848, Preprint: arXiv.2304.06582

[C] D. Teichrib and M. Schulze Darup. Error bounds for maxout neural network approximations of model predictive control, 22nd IFAC World Congress, pp. 10113-10119, 2023. DOI: 10.1016/j.ifacol.2023.10.883, Preprint: arXiv:2304.08779

[A] J. van Randenborgh and M. Schulze Darup. A tailored model for sustainable control of ATES systems using mixed-integer programming, Geothermiekongress 2023, Essen, 2023.

[A] M. Klädtke and M. Schulze Darup. Implicit predictors in regularized data-driven predictive control, 2023er Sitzung des GAMM-Fachausschuss Dynamik und Regelungstheorie, TU Dortmund, 2023.

[A] P. Binfet and M. Schulze Darup. Towards privacy-preserving cooperative control via encrypted distributed optimization, 2023er Sitzung des GAMM-Fachausschuss Dynamik und Regelungstheorie, TU Dortmund, 2023.

[A] J. van Randenborgh and M. Schulze Darup. Towards reliable predictive control for aquifer thermal energy storages, 2023er Sitzung des GAMM-Fachausschuss Dynamik und Regelungstheorie, TU Dortmund, 2023.

[A] P. Binfet and M. Schulze Darup. Privacy-Preserving Cooperative Control via Encrypted Distributed Optimization, 2023er Sitzung des GMA-Fachausschuss 2.15, Schloss Reisensburg, 2023.

[A] N. Schlüter and M. Schulze Darup. Verschlüsselte Regelungstechnik 2.0, 58. Regelungstechnisches Kolloquium in Boppard, 2023.

 

 

[J] N. Schlüter and M. Schulze Darup. On the stability of linear dynamic controllers with integer coefficients, IEEE Transactions on Automatic Control, 67(10): pp. 5610-5613, 2022. DOI: 10.1109/TAC.2021.3131126

[J] M. Schulze Darup, G. Book, D. E. Quevedo, and M. Nagahara. Fast hands-off control using ADMM real-time iterations, IEEE Transactions on Automatic Control, 67(10): pp. 5416-5423, 2022. DOI: 10.1109/TAC.2021.3121255

[C] M. Klädtke, D. Teichrib, N. Schlüter, and M. Schulze Darup. A deterministic view on explicit data-driven (M)PC, in Proc. of the 61st IEEE Conference on Decision and Control (CDC), pp. 499-504, 2022. DOI: 10.1109/CDC51059.2022.9993384, Preprint: arXiv:2206.07025

[C] Nils Schlü­ter, Philipp Binfet, Junsoo Kim, and Moritz Schulze Darup. Encrypted distributed state estimation via affine averaging, in Proc. of the 61st IEEE Conference on Decision and Control (CDC), pp. 7754-7761, 2022. DOI: 10.1109/CDC51059.2022.9992840, Preprint: arXiv:2209.07206

[C] J. Kim, M. Schulze Darup, and H. Sandberg, and K. H. Johansson. Asymptotic stabilization over encrypted data with limited controller capacity and time-varying quantizer, in Proc. of the 61st IEEE Conference on Decision and Control (CDC), pp. 7762-7767, 2022. DOI: 10.1109/CDC51059.2022.9993215

[C] N. Schlüter, M. Neuhaus, and M. Schulze Darup. Encrypted extremum seeking for privacy-preserving PID tuning as-a-Service, in Proc. of the 2022 European Control Conference (ECC), pp. 1288-1293, 2022. DOI: 10.23919/ECC55457.2022.9838380, Preprint: arXiv.2207.04442

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

[C] M. Klädtke and M. Schulze Darup. Convex reformulations for a special class of nonlinear MPC problems, in Proc. of the 2022 European Control Conference (ECC), pp. 761-768, 2022. DOI: 10.23919/ECC55457.2022.9838061. Preprint: arXiv.2206.08617

[A] M. Klädtke, D. Teichrib, N. Schlüter, and M. Schulze Darup. A note on explicit data-driven (M)PC , 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS), 2022. DOI: 10.15495/EPub_UBT_00006809.

[A] M. Nagahara, M. Schulze Darup, and Daniel E. Quevedo. Discrete-time hands-off feedback control with real-time optimization, 25th International Symposium on Mathematical Theory of Networks and Systems (MTNS), 2022. DOI: 10.15495/EPub_UBT_00006809.

[A] P. Binfet, N. Schlüter, D. Teichrib, M. Klädtke, and M. Schulze Darup. Towards encrypted data-driven (M)PC via explicit controller representations, 15th Viennese Conference on Optimal Control and Dynamic Games, 2022.

[J] M. Schulze Darup, A. B. Alexandru, G. J. Pappas, and D. Quevedo. Encrypted control for networked systems - An illustrative introduction and current challenges, IEEE Control Systems Magazine, 41(3): pp. 58–78, 2021. DOI: 10.1109/MCS.2021.3062956, Preprint: arXiv:2010.00268

[B] M. Schulze Darup and G. Book. On closed-loop dynamics of ADMM-based MPC, in Recent Advances in Model Predictive Control, T. Faulwasser, M. A. Müller, and K. Worthmann (Eds.), Springer, 2021. DOI: 10.1007/978-3-030-63281-6_5, Preprint: arXiv:1911.02641

[C] K. Tjell, N. Schlü­ter, P. Binfet, and M. Schulze Darup. Secure learning-based MPC via garbled circuit, in Proc. of the 60th IEEE Conference on Decision and Control (CDC), pp. 4907-4914, 2021. DOI: 10.1109/CDC45484.2021.9683540, Preprint: arXiv:2112.03654

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

[C] 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), pp. 294-299, 2021. DOI: 10.1016/j.ifacol.2021.08.559

[C] T. Faulwasser, S. Lucia, M. Schulze Darup, and M. Mönnigmann. Teaching MPC: Which way to the promised land?, in Proc. of the 7th IFAC Conference on Nonlinear Model Predictive Control (NMPC), pp. 240-245, 2021. DOI: 10.1016/j.ifacol.2021.08.551, Preprint: arXiv:2106.00944

[C] N. Schlü­ter, M. Neuhaus, and M. Schulze Darup. Encrypted dynamic control with unlimited operating time via FIR filters, in Proc. of the 2021 European Control Conference (ECC), pp. 952-957, 2021. DOI: 10.23919/ECC54610.2021.9655161, Preprint: arXiv:2112.02931

[A] N. Schlüter and M. Schulze Darup. Über verschlüsselte dynamische Regelungen und FIR-Filter, 2021er Sitzung des GMA-Fachausschuss 1.40 (GMA), Anif, 2021.

[A] D. Teichrib and M. Schulze Darup. Maßgeschneiderte neuronale Netze für modellprädiktive Regler, 2021er Sitzung des GMA-Fachausschuss 1.40 (GMA), Anif, 2021.

[J] M. Schulze Darup. Encrypted polynomial control based on tailored two-party computation, International Journal of Robust and Nonlinear Control, 30(11): pp. 4168-4187, 2020. DOI: 10.1002/rnc.5003

[B] M. Schulze Darup. Encrypted model predictive control in the cloud, in Privacy in Dynamical Systems, F. Farokhi (Ed.), Springer, 2020. DOI: 10.1007/978-981-15-0493-8_11

[C] N. Schlüter and M. Schulze Darup. Encrypted explicit MPC based on two-party computation and convex controller decomposition, in Proc. of the 59th IEEE Conference on Decision and Control (CDC), pp. 5469-5476, 2020. DOI: 10.1109/CDC42340.2020.9304078

[C] M. Neuhaus, S. Kollan, J. Bickendorf, and A. Müller. Methodology for choosing the best suitable strategy of robot trajectory adjustment, in Proc. of the 52nd International Symposium on Robotics (ISR), pp. 273-279, 2020. IEEE Xplore ID: 9307482

[C] N. Schlüter and M. Schulze Darup. Novel convex decomposition of piecewise affine functions, in Proc. of the 21st IFAC World Congress, 2020. Reprint: arXiv:2108.03950

[C] M. Schulze Darup. Encrypted MPC based on ADMM real-time iterations, in Proc. of the 21st IFAC World Congress, pp. 3508-3514, 2020. DOI: 10.1016/j.ifacol.2020.12.1708

[C] M. Schulze Darup. Exact representation of piecewise affine functions via neural networks, in Proc. of the 2020 European Control Conference (ECC), pp. 1073-1078, 2020. DOI: 10.23919/ECC51009.2020.9143957