Publications

[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 (in press). 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 (accepted).

[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 (accepted). Preprint: arXiv.2311.05215

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

[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. 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, 2023. 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, 2023. 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