This image shows Julian Berberich

Julian Berberich

Dr.-Ing.

Lecturer (Akademischer Rat)
Institute for Systems Theory and Automatic Control

Contact

+49 711 685 67747
 +49 711 685 67735

Pfaffenwaldring 9
70569 Stuttgart
Germany
Room: 2.235

Office Hours

Monday 1pm to 2pm in my office

Subject

My research explores concepts and methods of systems and control theory in quantum computing, studying theoretical properties of quantum computing elements and finding practical methods for improving their reliability. This includes, for example, the analysis of intrinsic properties of quantum algorithms such as robustness against hardware errors, modularity, and feedback mechanisms, as well as specific algorithm classes, e.g., in quantum machine learning. Further, I develop efficient and robust methods for estimation and control tasks which arise in real-world quantum hardware implementations.
 

Google Scholar profile

  1. (Journal-) Articles

    1. Strässer, Robin ; Schaller, Manuel ; Worthmann, Karl ; Berberich, Julian ; Allgöwer, Frank: Koopman-based feedback design with stability guarantees. In: IEEE Transactions on Automatic Control Bd. 70 (2025), S. 355–370
    2. Strässer, Robin ; Berberich, Julian ; Schaller, Manuel ; Worthmann, Karl ; Allgöwer, Frank: Koopman-based control of nonlinear systems with closed-loop guarantees. In: at-Automatisierungstechnik, Preprint: arxiv:2411.10359 (2025)
    3. Strässer, Robin ; Schaller, Manuel ; Berberich, Julian ; Worthmann, Karl ; Allgöwer, Frank: Kernel-based error bounds of bilinear Koopman surrogate models for nonlinear data-driven control. In: submitted, Preprint: arxiv:2503.13407 (2025)
    4. Berberich, J. ; Fink, D. ; Holm, C.: Robustness of quantum algorithms against coherent control errors. In: Physical Review A Bd. 109 (2024), S. 12417
    5. Funcke, Niklas ; Berberich, Julian: Robustness of optimal quantum annealing protocols. In: New Journal of Physics Bd. 26, IOP Publishing (2024), S. 93040
    6. Hertneck, Michael ; Lang, Simon ; Berberich, Julian ; Allgöwer, Frank: Event-Triggered Control Based on Integral Quadratic Constraints. In: IEEE Control Systems Letters Bd. 8 (2024), S. 2039–2044
    7. Venkatasubramanian, J. ; Köhler, J. ; Berberich, J. ; Allgöwer, F.: Sequential learning and control: Targeted exploration for robust performance. In: IEEE Trans. Automat. Control Bd. 70 (2024), S. 1–16
    8. Berberich, J. ; Fink, D. ; Pranjić, D. ; Tutschku, C. ; Holm, C.: Training robust and generalizable quantum models. In: Physical Review Research Bd. 6 (2024), S. 43326
    9. Berberich, J. ; Fink, D.: Quantum computing through the lens of control: A tutorial introduction. In: IEEE Control Systems Bd. 44 (2024), S. 24–49
    10. Strässer, Robin ; Schaller, Manuel ; Worthmann, Karl ; Berberich, Julian ; Allgöwer, Frank: SafEDMD: A certified learning architecture tailored to data-driven control of nonlinear dynamical systems. In: submitted, Preprint: arxiv:2402.03145 (2024)
    11. Bongard, J. ; Berberich, J. ; Köhler, J. ; Allgöwer, F.: Robust stability analysis of a simple data-driven model predictive control approach. In: IEEE Trans. Automat. Control Bd. 68 (2023), S. 2625–2637
    12. Berberich, J. ; Scherer, C. W. ; Allgöwer, F.: Combining prior knowledge and data for robust controller design. In: IEEE Trans. Automat. Control Bd. 68 (2023), S. 4618–4633
    13. Wang, Xin ; Sun, Jian ; Berberich, Julian ; Wang, Gang ; Allgöwer, Frank ; Chen, Jie: Data-driven Control of Dynamic Event-triggered Systems with Delays. In: Int. J. Robust and Nonlinear Control Bd. 33 (2023), S. 7071–7093
    14. Wang, Xin ; Berberich, Julian ; Sun, Jian ; Wang, Gang ; Allgöwer, Frank ; Chen, Jie: Model-based and data-driven control of event-and self-triggered discrete-time systems. In: IEEE Trans. Cybernetics Bd. 53 (2023), S. 6066–6079
    15. Alsalti, M. ; Lopez, V. G. ; Berberich, J. ; Allgöwer, F. ; Müller, M. A.: Data-based control of feedback linearizable systems. In: IEEE Trans. Automat. Control Bd. 68 (2023), S. 7014–7021
    16. Xie, Yifan ; Berberich, Julian ; Allgöwer, Frank: Linear Data-Driven Economic MPC with Generalized Terminal Constraint. In: IFAC World Congress (2023)
    17. Klöppelt, C. ; Berberich, J. ; Allgöwer, F. ; Müller, M. A.: A novel constraint-tightening approach for robust data-driven predictive control. In: Int. J. Robust and Nonlinear Control (2022)
    18. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Linear tracking MPC for nonlinear systems part II: the data-driven case. In: IEEE Trans. Automat. Control Bd. 67 (2022), S. 4406–4421. — extended version on arXiv:2105.08567
    19. Pauli, P. ; Berberich, J. ; Allgöwer, F.: Robustness analysis and training of recurrent neural networks using dissipativity theory. In: at - Automatisierungstechnik Bd. 70 (2022), S. 730–739
    20. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Linear tracking MPC for nonlinear systems part I: the model-based case. In: IEEE Trans. Automat. Control Bd. 67 (2022), S. 4390–4405
    21. Pauli, P. ; Koch, A. ; Berberich, J. ; Kohler, P. ; Allgöwer, F.: Training Robust Neural Networks using Lipschitz Bounds. In: IEEE Control Systems Lett. Bd. 6 (2021), S. 121–126
    22. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven model predictive control with stability and robustness guarantees. In: IEEE Trans. Automat. Control Bd. 66 (2021), S. 1702–1717
    23. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven model predictive control: closed-loop guarantees and experimental results. In: at-Automatisierungstechnik Bd. 69 (2021), S. 608–618
    24. Koch, Anne ; Berberich, Julian ; Köhler, Johannes ; Allgöwer, Frank: Determining optimal input–output properties: A data-driven approach. In: Automatica Bd. 134 (2021), S. 109906
    25. Pauli, Patricia ; Koch, Anne ; Berberich, Julian ; Kohler, Paul ; Allgöwer, Frank: Training Robust Neural Networks Using Lipschitz Bounds. In: IEEE Control Systems Letters Bd. 6, IEEE (2021), S. 121–126
    26. Koch, A. ; Berberich, J. ; Allgöwer, F.: Provably robust verification of dissipativity properties from data. In: IEEE Transactions on Automatic Control Bd. 67 (2021), S. 4248–4255
    27. Köhler, J. ; Schwenkel, L. ; Koch, A. ; Berberich, J. ; Pauli, P. ; Allgöwer, F.: Robust and optimal predictive control of the COVID-19 outbreak. In: Annual reviews in Control (2020). — to appear
    28. Berberich, J. ; Köhler, J. ; Allgöwer, F. ; Müller, M. A.: Dissipativity properties in constrained optimal control: A computational approach. In: Automatica Bd. 114 (2020), S. 108840
    29. Romer, A. ; Berberich, J. ; Köhler, J. ; Allgöwer, F.: One-shot verification of dissipativity properties from input-output data. In: IEEE Control Systems Lett. Bd. 3 (2019), S. 709–714
    30. Berberich, J. ; Dietrich, J. W. ; Hoermann, R. ; Müller, M. A.: Mathematical modeling of the pituitary-thyroid feedback loop: role of a TSH-T3-shunt and sensitivity analysis. In: Frontiers in Endocrinology Bd. 9 (2018), S. 91
    31. Berberich, J. ; Köhler, J. ; Allgöwer, F. ; Müller, M. A.: Indefinite Linear Quadratic Optimal Control: Strict Dissipativity and Turnpike Properties. In: IEEE Control Systems Lett. Bd. 2 (2018), S. 399–404

  2. Conferences

    1. Yifan Xie, Julian Berberich, Frank Allgöwer: Data-Driven Min-Max MPC for Linear Systems. In: , 2024, S. 3184–3189

  3. Conference papers

    1. Strässer, Robin ; Berberich, Julian ; Allgöwer, Frank: Koopman-based control using sum-of-squares optimization: Improved stability guarantees and data efficiency. In: Proc. European Control Conference (ECC), Preprint: arxiv:2411.03875, 2025
    2. Worthmann, Karl ; Strässer, Robin ; Schaller, Manuel ; Berberich, Julian ; Allgöwer, Frank: Data-driven MPC with terminal conditions in the Koopman framework. In: Proc. 63rd IEEE Conference on Decision and Control (CDC). Milan, Italy, 2024, S. 146–151
    3. Schneider, J. ; Berberich, J.: Using quantum computers in control: interval matrix properties. In: Proc. European Control Conf. (ECC). Stockholm, Sweden, 2024, S. 3841–3846
    4. Berberich, J. ; Kosut, R. L. ; Schulte-Herbrüggen, T.: Bringing quantum systems under control: a tutorial invitation to quantum computing and its relation to bilinear control systems. In: Proc. 63rd IEEE Conf. Decision and Control (CDC), 2024, S. 5231–5247
    5. Strässer, Robin ; Berberich, Julian ; Allgöwer, Frank: Robust data-driven control for nonlinear systems using the Koopman operator. In: Proc. 22nd IFAC World Congress. Bd. 56, 2023, S. 2257–2262
    6. Berberich, J. ; Iannelli, A. ; Padoan, A. ; Coulson, J. ; Dörfler, F. ; Allgöwer, F.: A quantitative and constructive proof of Willems‘ Fundamental Lemma and its implications. In: Proc. American Control Conf. (ACC). San Diego, CA, USA, 2023, S. 4155–4160
    7. Strässer, Robin ; Berberich, Julian ; Allgöwer, Frank: Control of bilinear systems using gain-scheduling: Stability and performance guarantees. In: Proc. 62nd IEEE Conference on Decision and Control (CDC). Singapore, Singapore, 2023, S. 4674–4681
    8. Alsalti, M. ; Lopez, V. G. ; Berberich, J. ; Allgöwer, F. ; Müller, M. A.: Data-driven nonlinear predictive control for feedback linearizable systems. In: Proc. 22nd IFAC World Congress. Yokohama, Japan, 2023, S. 617–624
    9. Köhler, M. ; Berberich, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven distributed MPC of dynamically coupled linear systems. In: Proc. 25th Int. Symp. Math. Theory Netw. Syst. (MTNS). Bayreuth, Germany, 2022, S. 365–370
    10. Köhler, J. ; Wabersich, K. ; Berberich, J. ; Zeilinger, Melanie N.: State space models vs. multi-step predictors in predictive control: are state space models complicating safe data-driven designs? In: Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 491–498
    11. Müller, D. ; Feilhauer, J. ; Wickert, J. ; Berberich, J. ; Allgöwer, F. ; Sawodny, O.: Data-driven predictive disturbance observer for quasi continuum manipulators. In: Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 1816–1822
    12. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Stability in data-driven MPC: an inherent robustness perspective. In: Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 1105–1110
    13. Pauli, P. ; Gramlich, D. ; Berberich, J. ; Allgöwer, F.: Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers. In: Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, S. 3611–3618
    14. Pauli, P. ; Köhler, J. ; Berberich, J. ; Koch, A. ; Allgöwer, F.: Offset-free setpoint tracking using neural network controllers. In: Proc. 3rd Conf. on Learning for Dynamics and Control (L4DC). Zurich, Switzerland, 2021, S. 992–1003
    15. Wieler, Nils ; Berberich, Julian ; Koch, Anne ; Allgöwer, Frank: Data-Driven Controller Design via Finite-Horizon Dissipativity. In: Proceedings of the 3rd Conference on Learning for Dynamics and Control, Proceedings of Machine Learning Research. Bd. 144 : PMLR, 2021, S. 287–298
    16. Berberich, J. ; Wildhagen, S. ; Hertneck, M. ; Allgöwer, F.: Data-driven analysis and control of continuous-time systems under aperiodic sampling. In: Proc. 19th IFAC Symp. System Identification (SYSID). Padova, Italy, 2021, S. 210–215
    17. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: On the design of terminal ingredients for data-driven MPC. In: Proc. 7th IFAC Conf. Nonlinear Model Predictive Control (NMPC). Bratislava, Slovakia, 2021, S. 257–263
    18. Alsalti, M. ; Berberich, J. ; Lopez, V. G. ; Allgöwer, F. ; Müller, M. A.: Data-Based System Analysis and Control of Flat Nonlinear Systems. In: Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, S. 1484–1489
    19. Venkatasubramanian, Janani ; Köhler, Johannes ; Berberich, Julian ; Allgöwer, Frank: Robust dual control based on gain scheduling. In: 2020 59th IEEE Conference on Decision and Control (CDC) : IEEE, 2021, S. 2270–2277
    20. Strässer, R. ; Berberich, J. ; Allgöwer, F.: Data-Driven Control of Nonlinear Systems: Beyond Polynomial Dynamics. In: Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, S. 4344–4351
    21. Wildhagen, S. ; Berberich, J. ; Hirche, M. ; Allgöwer, F.: Improved stability conditions for systems under aperiodic sampling: model- and data-based analysis. In: Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, S. 5788–5794
    22. Koch, A. ; Berberich, J. ; Allgöwer, F.: Verifying dissipativity properties from noise-corrupted input-state data. In: Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju, South Korea, 2020, S. 616–621
    23. Berberich, J. ; Koch, A. ; Scherer, C. W. ; Allgöwer, F.: Robust data-driven state-feedback design. In: Proc. American Control Conf. (ACC). Denver, CO, USA, 2020, S. 1532–1538
    24. Venkatasubramanian, J ; Köhler, J. ; Berberich, J. ; Allgöwer, F.: Robust dual control based on gain scheduling. In: Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 2270–2277
    25. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Robust constraint satisfaction in data-driven MPC. In: Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 1260–1267
    26. Berberich, J. ; Allgöwer, F.: A trajectory-based framework for data-driven system analysis and control. In: Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, S. 1365–1370
    27. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven tracking MPC for changing setpoints. In: Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 971–976
    28. Berberich, J. ; Sznaier, M. ; Allgöwer, F.: Signal estimation and system identification with nonlinear dynamic sensors. In: 3rd IEEE Conf. Control Technology and Applications (CCTA). Hong Kong, China, 2019, S. 505–510

Summer term
Model Predictive Control
Nonlinear control

Winter term
Data-driven control
Quantum Computing for Engineers

Since 06/2022 Lecturer (akademischer Rat) at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany.
02/2022-05/2022

Visiting researcher at the Automatic Control Laboratory, ETH Zürich, Switzerland.
03/2018-05/2022

Research and teaching assistant at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany.

  • PhD Thesis:
    "Stability and robustness in data-driven predictive control"
01/2017−06/2017 Exchange studies at the KTH Stockholm, Sweden.
06/2016-02/2018 Student assistant at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany.
10/2015-02/2018

Studies in Engineering Cybernetics (M.Sc.) at the University of Stuttgart, Germany.

  • Master Thesis:
    "Indefinite linear quadratic optimal control: Periodic dissipativity and turnpike properties"
10/2012-09/2015

Cooperative studies in Electrical Engineering (B.Eng.) at the DHBW Mannheim, Germany, in cooperation with WITTENSTEIN SE, Igersheim, Germany.

  • Bachelor Thesis:
    "Entwicklung und Implementierung eines geberlosen Anlaufverfahrens für permanentmagneterregte Synchronmaschinen durch Messung von raumzeigermodulierten Spannungssignalen im Spannungsbereich bis 60 V"

         

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