Dr. rer. nat. Dimitrios Karachalios

@article{doi:10.1137/22M153567X,
author = {Karachalios, D. S. and Gosea, I. V. and Gkimisis, L. and Antoulas, A. C.},
title = {Data-Driven Quadratic Modeling in the Loewner Framework from Input-Output Time-Domain Measurements},
journal = {SIAM Journal on Applied Dynamical Systems},
volume = {24},
number = {1},
pages = {457-500},
year = {2025},
doi = {10.1137/22M153567X},
URL = {    
   https://doi.org/10.1137/22M153567X
},
eprint = {  
        https://doi.org/10.1137/22M153567X},
    abstract = { Abstract.In this study, we present a purely data-driven method that uses the Loewner framework along with nonlinear optimization techniques to infer quadratic dynamical systems with affine control that admit Volterra series (VS) representations from input-output time-domain measurements. The proposed method extensively employs optimization tools for interpolating the symmetric generalized frequency response functions (GFRFs) derived in the VS framework. The GFRF estimations are obtained from the Fourier spectrum (phase and amplitude) of the quasi-steady-state system response under harmonic excitation. Appropriate treatment of these measurements under the developed framework allows the identification of low-order in-state dimension quadratic state-space models with nontrivial stable equilibria, such as in the Lorenz ’63 forced system. We thus can achieve low-order global model identification for certain classes of systems that can bifurcate to multiple equilibria after collecting measurements solely from a local stable operational regime. The advanced framework rigorously tests the identification and reduction features across various examples with increasing dimensions and varying complexities. It effectively addresses the inference of a reduced model from measurements of a viscous flow, assuming adherence to the Burgers’ model with Robin boundary conditions. These results provide new prospects for developing low-order predictive models based on input-output data suitable for control. }
}

@article{GOSEA2023234,
title = {A data-driven nonlinear frequency response approach based on the Loewner framework: preliminary analysis},
journal = {IFAC-PapersOnLine},
volume = {56},
number = {1},
pages = {234-239},
year = {2023},
note = {12th IFAC Symposium on Nonlinear Control Systems NOLCOS 2022},
issn = {2405-8963},
doi = {https://doi.org/10.1016/j.ifacol.2023.02.040},
url = {https://www.sciencedirect.com/science/article/pii/S2405896323002288},
author = {Ion Victor Gosea and Luka A. Živković and Dimitrios S. Karachalios and Tanja Vidaković-Koch and Athanasios C. Antoulas},
keywords = {Data-Driven Methods, Nonlinear Dynamics, Nonlinear Frequency Response, Transfer Functions, Frequency Response Functions, Model Reduction, Non-intrusive Approach}
}

@misc{karachalios2023error,
      title = {Error Bounds in Nonlinear Model Predictive Control with Linear Differential Inclusions of Parametric-Varying Embeddings}, 
      author={Dimitrios S. Karachalios and Maryam Nezami and Georg Schildbach and Hossameldin S. Abbas},
      year={2023},
      eprint={2310.01049},
      archivePrefix={arXiv},
      primaryClass={math.OC}
}

@Inproceedings{Nezami2023,
author = {Maryam Nezami and Dimitrios S. Karachalios and Georg Schildbach and Hossam S. Abbas},
title = {On the Design of Nonlinear MPC and LPVMPC for Obstacle Avoidance in Autonomous Driving},
booktitle = {International Conference on Control, Decision and Information Technologies (CoDIT)(accepted)},
year = {2023},
month = {July},
address = {Italy}
 url = {https://arxiv.org/pdf/2307.06031.pdf}
}

@misc{KGGA2022,
  doi = {10.48550/ARXIV.2211.10635},
  url = {https://arxiv.org/abs/2211.10635},
  author = {Karachalios, D. S. and Gosea, I. V. and Gkimisis, L. and Antoulas, A. C.},
  keywords = {Dynamical Systems (math.DS), FOS: Mathematics, FOS: Mathematics, 93B15, 93C15, 93C10, 65F45},
  title = {Data-driven quadratic modeling in the Loewner framework},
  publisher = {arXiv},
  note = {Submitted to SIADS Journal 17.11.2022, status: In Review},
  year = {2022},
  copyright = {arXiv.org perpetual, non-exclusive license}
}

@misc{karachalios2022bilinear,
      title={Bilinear realization from input-output data with neural networks}, 
      author={Dimitrios S. Karachalios and Ion Victor Gosea and Kirandeep Kour and Athanasios C. Antoulas},
      year={2022},
      eprint={2208.10124},
      archivePrefix={arXiv},
      primaryClass={math.DS}
}

@article{KARACHALIOS20227,
title = {A framework for fitting quadratic-bilinear systems with applications to models of electrical circuits},
journal = {IFAC-PapersOnLine},
volume = {55},
number = {20},
pages = {7-12},
year = {2022},
note = {10th Vienna International Conference on Mathematical Modelling MATHMOD 2022},
issn = {2405-8963},
doi = {https://doi.org/10.1016/j.ifacol.2022.09.064},
url = {https://www.sciencedirect.com/science/article/pii/S2405896322012459},
author = {Dimitrios S. Karachalios and Ion Victor Gosea and Athanasios C. Antoulas},
keywords = {Data-Driven, Non-Intrusive Modeling, Model Order Reduction, Nonlinear Dynamics, Quadratic-Bilinear Systems, System Identification, Lift, Learn Approach}
}

@article{BennerFilanovaKarachaliosMonemAbdelhafezPrzybillaWerner+2021+198+204,
url = {https://doi.org/10.1515/dmvm-2021-0075},
title = {Mathematische Komplexitätsreduktion: Modellreduktion dynamischer Systeme},
title = {},
author = {Peter Benner and Yevgeniya Filanova and Dimitrios Karachalios and Shaimaa Monem Abdelhafez and Jennifer Przybilla and Steffen W. R. Werner},
pages = {198--204},
volume = {29},
number = {4},
journal = {Mitteilungen der Deutschen Mathematiker-Vereinigung},
doi = {doi:10.1515/dmvm-2021-0075},
year = {2021},
lastchecked = {2023-04-17}
}

@inbook{KarachaliosGoseaAntoulas+2021+181+228,
url = {https://doi.org/10.1515/9783110498967-006},
title = {6 The Loewner framework for system identification and reduction},
booktitle = {Volume 1 System- and Data-Driven Methods and Algorithms},
author = {Dimitrios S. Karachalios and Ion Victor Gosea and Athanasios C. Antoulas},
editor = {Peter Benner and Stefano Grivet-Talocia and Alfio Quarteroni and Gianluigi Rozza and Wil Schilders and Luís Miguel Silveira},
publisher = {De Gruyter},
address = {Berlin, Boston},
pages = {181--228},
doi = {doi:10.1515/9783110498967-006},
isbn = {9783110498967},
year = {2021},
lastchecked = {2023-04-17}
}

@article{https://doi.org/10.1002/pamm.202000346,
author = {Karachalios, Dimitrios S. and Gosea, Ion Victor and Antoulas, Athanasios C.},
title = {Data-driven (Bilinear) identification and reduction},
journal = {PAMM},
volume = {20},
number = {S1},
pages = {e202000346},
doi = {https://doi.org/10.1002/pamm.202000346},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.202000346},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.202000346},
year = {2021}
}

@INPROCEEDINGS{9654993,
  author={Gosea, Ion Victor and Karachalios, Dimitrios S. and Antoulas, Athanasios C.},
  booktitle={2021 European Control Conference (ECC)}, 
  title={Learning reduced-order models of quadratic dynamical systems from input-output data}, 
  year={2021},
  volume={},
  number={},
  pages={1426-1431},
  doi={10.23919/ECC54610.2021.9654993}
}

@article{BennerFilanovaKarachaliosMonemAbdelhafezPrzybillaWerner+2021+198+204,
url = {https://doi.org/10.1515/dmvm-2021-0075},
title = {Mathematische Komplexitätsreduktion: Modellreduktion dynamischer Systeme},
title = {},
author = {Peter Benner and Yevgeniya Filanova and Dimitrios Karachalios and Shaimaa Monem Abdelhafez and Jennifer Przybilla and Steffen W. R. Werner},
pages = {198--204},
volume = {29},
number = {4},
journal = {Mitteilungen der Deutschen Mathematiker-Vereinigung},
doi = {doi:10.1515/dmvm-2021-0075},
year = {2021},
lastchecked = {2023-04-17}
}

@Inbook{Karachalios2021,
author="Karachalios, D. S.
and Gosea, I. V.
and Antoulas, A. C.",
editor="Benner, Peter
and Breiten, Tobias
and Fa{\ss}bender, Heike
and Hinze, Michael
and Stykel, Tatjana
and Zimmermann, Ralf",
title="On Bilinear Time-Domain Identification and Reduction in the Loewner Framework",
bookTitle="Model Reduction of Complex Dynamical Systems",
year={2021},
publisher="Springer International Publishing",
address="Cham",
pages="3--30",
doi="10.1007/978-3-030-72983-7_1",
url="https://doi.org/10.1007/978-3-030-72983-7_1"
}

@article{https://doi.org/10.1002/pamm.202100254,
author = {Gosea, Ion Victor and Karachalios, Dimitrios S. and Antoulas, Athanasios C.},
title = {On computing reduced-order bilinear models from time-domain data},
journal = {PAMM},
volume = {21},
number = {1},
pages = {e202100254},
doi = {https://doi.org/10.1002/pamm.202100254},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.202100254},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.202100254},
year = {2021}
}

@article{https://doi.org/10.1002/pamm.202000337,
author = {Karachalios, Dimitrios S. and Gosea, Ion Victor and Antoulas, Athanasios C.},
title = {The Loewner framework for nonlinear identification and reduction of Hammerstein cascaded dynamical systems},
journal = {PAMM},
volume = {20},
number = {1},
pages = {e202000337},
doi = {https://doi.org/10.1002/pamm.202000337},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.202000337},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.202000337},
year = {2021}
}

@article{https://doi.org/10.1002/pamm.201900246,
author = {Karachalios, Dimitrios S. and Gosea, Ion Victor and Antoulas, Athanasios C.},
title = {A bilinear identification-modeling framework from time domain data},
journal = {PAMM},
volume = {19},
number = {1},
pages = {e201900246},
doi = {https://doi.org/10.1002/pamm.201900246},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.201900246},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.201900246},
year = {2019}
}

@article{https://doi.org/10.1002/pamm.201800368,
author = {Karachalios, Dimitrios S. and Gosea, Ion Victor and Antoulas, Athanasios C.},
title = {Data-driven approximation methods applied to non-rational functions},
journal = {PAMM},
volume = {18},
number = {1},
pages = {e201800368},
doi = {https://doi.org/10.1002/pamm.201800368},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.201800368},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/pamm.201800368},
year = {2018}
}

@misc{karachalios2017case,
      title={Case study: Approximations of the Bessel Function}, 
      author={D. S. Karachalios and I. V. Gosea and Q. Zhang and A. C. Antoulas},
      year={2017},
      eprint={1801.03390},
      archivePrefix={arXiv},
      primaryClass={math.NA}
}