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

On appointment

Subject

My research interests are centered around systems and control theory with a focus on 
  • data-driven and learning-based control: deriving theoretical guarantees for the closed loop, also in the presence of noisy data or nonlinearities;
  • quantum computing through the lens of control theory: studying robustness of quantum algorithms.

Google Scholar profile

  1. (Journal-) Articles

    1. 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, IEEE Trans. Automat. Control. Bd. 68 (2023), Nr. 5, S. 2625–2637
    2. Berberich, J. ; Scherer, C. W. ; Allgöwer, F.: Combining prior knowledge and data for robust controller design. In: IEEE Trans. Automat. Control, IEEE Trans. Automat. Control. Bd. 68 (2023), Nr. 8, S. 4618–4633
    3. 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, Int. J. Robust and Nonlinear Control. Bd. 33 (2023), S. 7071–7093
    4. Xie, Yifan ; Berberich, Julian ; Allgöwer, Frank: Linear Data-Driven Economic MPC with Generalized Terminal Constraint. In: IFAC World Congress, IFAC World Congress. (2023)
    5. Alsalti, M. ; Lopez, V. G. ; Berberich, J. ; Allgöwer, F. ; Müller, M. A.: Data-based control of feedback linearizable systems. In: IEEE Trans. Automat. Control, IEEE Trans. Automat. Control. (2023). — accepted, preprint: arXiv:2204.01148
    6. Pauli, P. ; Berberich, J. ; Allgöwer, F.: Robustness analysis and training of recurrent neural networks using dissipativity theory. In: at - Automatisierungstechnik, at - Automatisierungstechnik. Bd. 70 (2022), Nr. 8, S. 730–739
    7. 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, IEEE Trans. Automat. Control. Bd. 67 (2022), Nr. 9, S. 4406–4421. — extended version on arXiv:2105.08567
    8. 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, Int. J. Robust and Nonlinear Control. (2022)
    9. 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, IEEE Trans. Automat. Control. Bd. 67 (2022), Nr. 9, S. 4390–4405
    10. Pauli, P. ; Koch, A. ; Berberich, J. ; Kohler, P. ; Allgöwer, F.: Training Robust Neural Networks using Lipschitz Bounds. In: IEEE Control Systems Lett., IEEE Control Systems Lett. Bd. 6 (2021), S. 121–126
    11. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven model predictive control with stability and robustness guarantees. In: IEEE Trans. Automat. Control, IEEE Trans. Automat. Control. Bd. 66 (2021), Nr. 4, S. 1702–1717
    12. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven model predictive control: closed-loop guarantees and experimental results. In: at-Automatisierungstechnik, at-Automatisierungstechnik. Bd. 69 (2021), Nr. 7, S. 608–618
    13. Koch, Anne ; Berberich, Julian ; Köhler, Johannes ; Allgöwer, Frank: Determining optimal input–output properties: A data-driven approach. In: Automatica, Automatica. Bd. 134 (2021), S. 109906
    14. Pauli, Patricia ; Koch, Anne ; Berberich, Julian ; Kohler, Paul ; Allgöwer, Frank: Training Robust Neural Networks Using Lipschitz Bounds. In: IEEE Control Systems Letters, IEEE Control Systems Letters. Bd. 6, IEEE (2021), S. 121–126
    15. Wang, Xin ; Berberich, Julian ; Sun, Jian ; Wang, Gang ; Allgöwer, Frank ; Chen, Jie: Data-Driven Control of Event-and Self-Triggered Discrete-Time Systems. In: Automatica, Automatica. (2021). — submitted, preprint: arXiv:2202.08019
    16. Koch, A. ; Berberich, J. ; Allgöwer, F.: Provably robust verification of dissipativity properties from data. In: IEEE Transactions on Automatic Control, IEEE Transactions on Automatic Control. Bd. 67 (2021), Nr. 8, S. 4248–4255
    17. 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, Annual reviews in Control. (2020). — to appear
    18. Berberich, J. ; Köhler, J. ; Allgöwer, F. ; Müller, M. A.: Dissipativity properties in constrained optimal control: A computational approach. In: Automatica, Automatica. Bd. 114 (2020), S. 108840
    19. Romer, A. ; Berberich, J. ; Köhler, J. ; Allgöwer, F.: One-shot verification of dissipativity properties from input-output data. In: IEEE Control Systems Lett., IEEE Control Systems Lett. Bd. 3 (2019), S. 709–714
    20. 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, Frontiers in Endocrinology. Bd. 9 (2018), S. 91
    21. Berberich, J. ; Köhler, J. ; Allgöwer, F. ; Müller, M. A.: Indefinite Linear Quadratic Optimal Control: Strict Dissipativity and Turnpike Properties. In: IEEE Control Systems Lett., IEEE Control Systems Lett. Bd. 2 (2018), Nr. 3, S. 399–404

  2. Conferences

    1. Yifan Xie, Julian Berberich, Frank Allgöwer: Data-Driven Min-Max MPC for Linear Systems. In: , 2023

  3. Conference papers

    1. 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), Proc. American Control Conf. (ACC). San Diego, CA, USA, 2023, S. 4155–4160
    2. Strässer, Robin ; Berberich, Julian ; Allgöwer, Frank: Robust data-driven control for nonlinear systems using the Koopman operator. In: Proc. 22nd IFAC World Congress, Proc. 22nd IFAC World Congress. Bd. 56, 2023, S. 2257–2262
    3. Strässer, Robin ; Berberich, Julian ; Allgöwer, Frank: Control of bilinear systems using gain-scheduling: Stability and performance guarantees. In: 62nd IEEE Conference on Decision and Control (accepted), Preprint: arXiv:2304.04486, 62nd IEEE Conference on Decision and Control (accepted), Preprint: arXiv:2304.04486, 2023
    4. 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), Proc. 25th Int. Symp. Math. Theory Netw. Syst. (MTNS). Bayreuth, Germany, 2022, S. 365–370
    5. 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), Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 491–498
    6. 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), Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 1816–1822
    7. 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), Proc. 61st IEEE Conf. Decision and Control (CDC). Cancun, Mexico, 2022, S. 1105–1110
    8. 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), Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, S. 5788–5794
    9. 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), Proc. 19th IFAC Symp. System Identification (SYSID). Padova, Italy, 2021, S. 210–215
    10. 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), Proc. 60th IEEE Conf. on Decision and Control (CDC). Austin, TX, USA, 2021, S. 3611–3618
    11. 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), Proc. 3rd Conf. on Learning for Dynamics and Control (L4DC). Zurich, Switzerland, 2021, S. 992–1003
    12. 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 the 3rd Conference on Learning for Dynamics and Control. Bd. 144 : PMLR, 2021, S. 287--298
    13. 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), Proc. 7th IFAC Conf. Nonlinear Model Predictive Control (NMPC). Bratislava, Slovakia, 2021, S. 257–263
    14. 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), Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, S. 1484–1489
    15. Strässer, R. ; Berberich, J. ; Allgöwer, F.: Data-Driven Control of Nonlinear Systems: Beyond Polynomial Dynamics. In: Proc. 60th IEEE Conf. Decision and Control (CDC), Proc. 60th IEEE Conf. Decision and Control (CDC). Austin, TX, USA, 2021, S. 4344–4351
    16. 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), 2020 59th IEEE Conference on Decision and Control (CDC) : IEEE, 2021, S. 2270–2277
    17. 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), Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 1260–1267
    18. Berberich, J. ; Koch, A. ; Scherer, C. W. ; Allgöwer, F.: Robust data-driven state-feedback design. In: Proc. American Control Conf. (ACC), Proc. American Control Conf. (ACC). Denver, CO, USA, 2020, S. 1532–1538
    19. Venkatasubramanian, J ; Köhler, J. ; Berberich, J. ; Allgöwer, F.: Robust dual control based on gain scheduling. In: Proc. 59th IEEE Conf. Decision and Control (CDC), Proc. 59th IEEE Conf. Decision and Control (CDC). Jeju, South Korea, 2020, S. 2270–2277
    20. Berberich, J. ; Köhler, J. ; Müller, M. A. ; Allgöwer, F.: Data-driven tracking MPC for changing setpoints. In: Proc. 21st IFAC World Congress, Proc. 21st IFAC World Congress. Berlin, Germany, 2020, S. 971–976
    21. 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), Proc. 59th IEEE Conf. on Decision and Control (CDC). Jeju, South Korea, 2020, S. 616–621
    22. Berberich, J. ; Allgöwer, F.: A trajectory-based framework for data-driven system analysis and control. In: Proc. European Control Conf. (ECC), Proc. European Control Conf. (ECC). Saint Petersburg, Russia, 2020, S. 1365–1370
    23. Berberich, J. ; Sznaier, M. ; Allgöwer, F.: Signal estimation and system identification with nonlinear dynamic sensors. In: 3rd IEEE Conf. Control Technology and Applications (CCTA), 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

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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