Publications

List of publications

  1. 2023

    1. V. Mehrmann and B. Unger, “Control of port-Hamiltonian differential-algebraic systems and applications,” Acta Numerica, vol. 32, pp. 395–515, 2023, doi: 10.1017/S0962492922000083.
    2. T. Holicki, J. Nicodemus, P. Schwerdtner, and B. Unger, “Energy matching in reduced passive and port-Hamiltonian systems,” 2023.
    3. R. Morandin, J. Nicodemus, and B. Unger, “Port-Hamiltonian Dynamic Mode Decomposition,” SIAM Journal on Scientific Computing, vol. 45, no. 4, Art. no. 4, Jul. 2023, doi: 10.1137/22m149329x.
  2. 2022

    1. F. Black, P. Schulze, and B. Unger, “Modal Decomposition of Flow Data via Gradient-Based Transport Optimization,” in Active Flow and Combustion Control 2021, R. King and D. Peitsch, Eds., in Active Flow and Combustion Control 2021. Cham: Springer International Publishing, 2022, pp. 203–224. doi: 10.1007/978-3-030-90727-3_13.
    2. V. Mehrmann and B. Unger, “Control of port-Hamiltonian differential-algebraic systems and applications,” ArXiv e-print 2201.06590, 2022, [Online]. Available: http://arxiv.org/abs/2201.06590
    3. T. Breiten, D. Hinsen, and B. Unger, “Towards a modeling class for port-Hamiltonian systems with time-delay,” 2022. doi: 10.48550/arXiv.2211.10687.
    4. D. Frank, D. A. Latif, M. Muehlebach, B. Unger, and S. Staab, “Robust Recurrent Neural Network to Identify Ship Motion in Open Water with Performance Guarantees,” Publication, 2022. doi: 10.48550/arXiv.2212.05781.
    5. J. Heiland and B. Unger, “Identification of Linear Time-Invariant Systems with Dynamic Mode Decomposition,” Mathematics, vol. 10, no. 3, Art. no. 3, 2022, doi: 10.3390/math10030418.
    6. B. Hillebrecht and B. Unger, “Certified machine learning: A posteriori error estimation for physics-informed neural networks,” ArXiv e-print 2203.17055, 2022, [Online]. Available: http://arxiv.org/abs/2203.17055
    7. B. Hillebrecht and B. Unger, “Certified machine learning: Rigorous a posteriori error bounds for PDE defined PINNs,” 2022.
    8. T. Breiten and B. Unger, “Passivity preserving model reduction via spectral factorization,” Automatica, vol. 142, p. 110368, Aug. 2022, doi: 10.1016/j.automatica.2022.110368.
    9. J. Nicodemus, J. Kneifl, J. Fehr, and B. Unger, “Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators,” IFAC-PapersOnLine, vol. 55, no. 20, Art. no. 20, 2022, doi: 10.1016/j.ifacol.2022.09.117.
    10. R. Altmann, R. Maier, and B. Unger, “Semi-explicit integration of second order for weakly coupled poroelasticity,” ArXiv e-print 2203.16664, 2022, [Online]. Available: http://arxiv.org/abs/2203.16664
    11. R. Morandin, J. Nicodemus, and B. Unger, “Port-Hamiltonian Dynamic Mode Decomposition,” ArXiv e-print 2204.13474, 2022, doi: 10.48550/arXiv.2204.13474.
  3. 2021

    1. R. Altmann, R. Maier, and B. Unger, “Semi-explicit discretization schemes for weakly coupled elliptic-parabolic problems,” Mathematics of Computation, vol. 90, no. 329, Art. no. 329, 2021, doi: 10.1090/mcom/3608.
    2. I. Ahrens and B. Unger, “A simple success check for delay differential-algebraic equations,” in Proceedings in Applied Mathematics and Mechanics 2020, in Proceedings in Applied Mathematics and Mechanics 2020, vol. 20. Wiley, 2021, p. e202000270. doi: 10.1002/pamm.202000270.
    3. F. Black, P. Schulze, and B. Unger, “Efficient Wildland Fire Simulation via Nonlinear Model Order Reduction,” Fluids, vol. 6, no. 8, Art. no. 8, 2021, doi: 10.3390/fluids6080280.
    4. I. V. Gosea, S. Gugercin, and B. Unger, “Parametric model reduction via rational interpolation along parameters,” in 2021 60th IEEE Conference on Decision and Control (CDC), in 2021 60th IEEE Conference on Decision and Control (CDC). 2021, pp. 6895–6900. doi: 10.1109/CDC45484.2021.9682841.
    5. F. Black, P. Schulze, and B. Unger, “Decomposition of flow data via gradient-based transport optimization,” ArXiv e-print 2107.03481, 2021, [Online]. Available: https://arxiv.org/abs/2107.03481
    6. R. Altmann, V. Mehrmann, and B. Unger, “Port-Hamiltonian formulations of poroelastic network models,” Mathematical and Computer Modelling of Dynamical Systems, vol. 27, no. 1, Art. no. 1, 2021, doi: 10.1080/13873954.2021.1975137.
    7. F. Black, P. Schulze, and B. Unger, “Model order reduction with dynamically transformed modes for the wave equation,” in Proceedings in Applied Mathematics and Mechanics 2020, in Proceedings in Applied Mathematics and Mechanics 2020, vol. 20. Wiley, 2021, p. e202000321. doi: 10.1002/pamm.202000321.
    8. J. Heiland and B. Unger, “Identification of linear time-invariant systems with Dynamic Mode Decomposition,” ArXiv e-print 2109.06765, 2021, [Online]. Available: https://arxiv.org/abs/2109.06765
    9. J. Nicodemus, J. Kneifl, J. Fehr, and B. Unger, “Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators,” ArXiv e-print 2109.10793, 2021, [Online]. Available: https://arxiv.org/abs/2109.10793
    10. S. Trenn and B. Unger, “Unimodular transformations for DAE initial trajectory problems,” in Proceedings in Applied Mathematics and Mechanics 2020, in Proceedings in Applied Mathematics and Mechanics 2020, vol. 20. Wiley, 2021, p. e202000322. doi: 10.1002/pamm.202000322.
    11. R. Altmann, R. Maier, and B. Unger, “A semi-explicit integration scheme for weakly-coupled poroelasticity with nonlinear permeability,” in Proceedings in Applied Mathematics and Mechanics 2020, in Proceedings in Applied Mathematics and Mechanics 2020, vol. 20. Wiley, 2021, p. e202000061. doi: 10.1002/pamm.202000061.
    12. T. Breiten and B. Unger, “Passivity preserving model reduction via spectral factorization,” ArXiv e-print 2103.13194, 2021, [Online]. Available: https://arxiv.org/abs/2103.13194
  4. 2020

    1. I. Ahrens and B. Unger, “The Pantelides algorithm for delay differential-algebraic equations,” Transactions of Mathematics and Its Application, vol. 4, no. 1, Art. no. 1, 2020, doi: 10.1093/imatrm/tnaa003.
    2. R. Altmann, R. Maier, and B. Unger, “Semi-explicit discretization schemes for weakly coupled elliptic-parabolic problems,” Mathematics of Computation, p. 1, Oct. 2020, doi: 10.1090/mcom/3608.
    3. F. Black, P. Schulze, and B. Unger, “Projection-based model reduction with dynamically transformed modes,” ESAIM: Mathematical Modelling and Numerical Analysis, vol. 54, no. 6, Art. no. 6, Oct. 2020, doi: 10.1051/m2an/2020046.
    4. R. Altmann, V. Mehrmann, and B. Unger, “Port-Hamiltonian formulations of poroelastic network models,” ArXiv e-print 2012.01949, Dec. 2020, [Online]. Available: https://arxiv.org/abs/2012.01949
    5. B. Unger, “Delay differential-algebraic equations in real-time dynamic substructuring,” ArXiv e-print 2003.10195, Mar. 2020, [Online]. Available: https://arxiv.org/abs/2003.10195
  5. 2019

    1. S. Trenn and B. Unger, “Delay regularity of differential-algebraic equations,” in 2019 IEEE 58th Conference on Decision and Control (CDC), in 2019 IEEE 58th Conference on Decision and Control (CDC). Dec. 2019, pp. 989–994. doi: 10.1109/CDC40024.2019.9030146.
    2. E. Fosong, P. Schulze, and B. Unger, “From Time-Domain Data to Low-Dimensional Structured Models,” ArXiv e-print 1902.05112, Feb. 2019, [Online]. Available: https://arxiv.org/abs/1902.05112
    3. B. Unger and S. Gugercin, “Kolmogorov n-widths for linear dynamical systems,” Advances in Computational Mathematics, vol. 45, no. 5, Art. no. 5, Dec. 2019, doi: 10.1007/s10444-019-09701-0.
    4. D. Kern, M. Bartelt, and B. Unger, “How to write an article for GAMMAS and a longer title,” GAMM Archive for Students, vol. 1, no. 1, Art. no. 1, Feb. 2019, doi: 10.14464/gammas.v1i1.417.
  6. 2018

    1. P. Schulze, B. Unger, Christopher. Beattie, and S. Gugercin, “Data-driven Structured Realization,” Linear Algebra and its Applications, vol. 537, pp. 250–286, 2018, doi: 10.1016/j.laa.2017.09.030.
    2. P. Schulze and B. Unger, “Model reduction for linear systems with low-rank switching.,” SIAM J. Control and Optimization, vol. 56, no. 6, Art. no. 6, 2018, doi: 10.1137/18M1167887.
    3. B. Unger, “Discontinuity Propagation in Delay Differential-Algebraic Equations,” The Electronic Journal of Linear Algebra, vol. 34, pp. 582–601, Feb. 2018, doi: 10.13001/1081-3810.3759.
  7. 2016

    1. P. Schulze and B. Unger, “Data-driven interpolation of dynamical systems with delay.,” Systems Control Lett., vol. 97, pp. 125–131, 2016, doi: 10.1016/j.sysconle.2016.09.007.
  8. 2015

    1. V. Mehrmann and B. Unger, “Index preserving polynomial representation of nonlinear differential-algebraic systems,” Institut für Mathematik, TU Berlin, Str. des 17. Juni 136, D-10623 Berlin, FRG, Preprint 2--2015, 2015. [Online]. Available: http://www3.math.tu-berlin.de/cgi-bin/IfM/show_abstract.cgi?Report-02-2015.rdf.html
  9. 2013

    1. B. Unger, “Impact of Discretization Techniques on Nonlinear Model Reduction and Analysis of the Structure of the POD Basis,” Master’s Thesis, Virginia Polytechnic and State University, Blacksburg, Virginia, USA, 2013. [Online]. Available: https://vtechworks.lib.vt.edu/handle/10919/24197
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