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 interests are centered around systems and control theory with a focus on quantum algorithms and data-driven control. In quantum algorithms, I am using systems and control theory to better understand questions of robustness, optimization, and machine learning, but I am also studying the converse direction of how to use quantum computers in control. In data-driven control, I am developing methods with rigorous stability and robustness guarantees to design safe controllers with high performance as required for complex control applications.
 

Google Scholar profile

  1. (Journal-) Articles

    1. 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)
    2. 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
    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. Funcke, N. ; Berberich, J.: Robustness of optimal quantum annealing protocols. In: New Journal of Physics Bd. 26 (2024), S. 93040
    5. Berberich, J. ; Fink, D. ; Holm, C.: Robustness of quantum algorithms against coherent control errors. In: Physical Review A Bd. 109 (2024), S. 12417
    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. 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
    18. 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
    19. 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)
    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. 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
    6. 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
    7. 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
    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. 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
    16. 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
    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. 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
    20. 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
    21. 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
    22. 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
    23. 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
    24. 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
    25. 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
    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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