Sebastian Peitz

Data Science for Engineering
sebastian.peitz@uni-paderborn.de
ID
47427

61 Publications

Mark all

[61]
2024 | Preprint | LibreCat-ID: 51160 | OA
Philipp, F. M., Schaller, M., Boshoff, S., Peitz, S., Nüske, F., & Worthmann, K. (2024). Extended Dynamic Mode Decomposition: Sharp bounds on the sample  efficiency. In arXiv:2402.02494.
LibreCat | Download (ext.) | arXiv
 
[60]
2024 | Journal Article | LibreCat-ID: 46019 | OA
Sonntag, K., & Peitz, S. (2024). Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications. https://doi.org/10.1007/s10957-024-02389-3
LibreCat | DOI | Download (ext.)
 
[59]
2024 | Preprint | LibreCat-ID: 51334 | OA
Sonntag, K., Gebken, B., Müller, G., Peitz, S., & Volkwein, S. (2024). A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. In arXiv:2402.06376.
LibreCat | Download (ext.) | arXiv
 
[58]
2024 | Journal Article | LibreCat-ID: 40171 | OA
Peitz, S., Stenner, J., Chidananda, V., Wallscheid, O., Brunton, S. L., & Taira, K. (2024). Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning. Physica D: Nonlinear Phenomena, 461, 134096. https://doi.org/10.1016/j.physd.2024.134096
LibreCat | DOI | Download (ext.)
 
[57]
2024 | Journal Article | LibreCat-ID: 33461 | OA
Otto, S. E., Peitz, S., & Rowley, C. W. (2024). Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories. SIAM Journal on Applied Dynamical Systems, 23(1), 885–923. https://doi.org/10.1137/22M1523601
LibreCat | DOI | Download (ext.) | arXiv
 
[56]
2024 | Journal Article | LibreCat-ID: 38031 | OA
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2024). Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis , 71, Article 101657. https://doi.org/10.1016/j.acha.2024.101657
LibreCat | DOI | Download (ext.) | arXiv
 
[55]
2023 | Journal Article | LibreCat-ID: 21199 | OA
Peitz, S., & Bieker, K. (2023). On the Universal Transformation of Data-Driven Models to Control Systems. Automatica, 149, Article 110840. https://doi.org/10.1016/j.automatica.2022.110840
LibreCat | DOI | Download (ext.)
 
[54]
2023 | Preprint | LibreCat-ID: 42160 | OA
Werner, S., & Peitz, S. (2023). Learning a model is paramount for sample efficiency in reinforcement  learning control of PDEs. In arXiv:2302.07160.
LibreCat | Download (ext.) | arXiv
 
[53]
2023 | Journal Article | LibreCat-ID: 27426 | OA
Gebken, B., Bieker, K., & Peitz, S. (2023). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization, 85(3), 709–741. https://doi.org/10.1007/s10898-022-01223-2
LibreCat | DOI | Download (ext.)
 
[52]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller, M., Worthmann, K., Philipp, F., Peitz, S., & Nüske, F. (2023). Towards reliable data-based optimal and predictive control using extended DMD. IFAC-PapersOnLine, 56(1), 169–174. https://doi.org/10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[51]
2023 | Preprint | LibreCat-ID: 46579 | OA
Peitz, S., Harder, H., Nüske, F., Philipp, F., Schaller, M., & Worthmann, K. (2023). Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems. In arXiv:2307.15325.
LibreCat | Download (ext.) | arXiv
 
[50]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske, F., Peitz, S., Philipp, F., Schaller, M., & Worthmann, K. (2023). Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science, 33, Article 14. https://doi.org/10.1007/s00332-022-09862-1
LibreCat | DOI | Download (ext.)
 
[49]
2023 | Preprint | LibreCat-ID: 46649 | OA
Hotegni, S. S., Peitz, S., & Berkemeier, M. B. (2023). Multi-Objective Optimization for Sparse Deep Neural Network Training. In arXiv:2308.12243.
LibreCat | Download (ext.) | arXiv
 
[48]
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, M., Hüllermeier, E., Lücke, M., Ober-Blöbaum, S., Offen, C., Peitz, S., & Pfannschmidt, K. (2023). Efficient time stepping for numerical integration using reinforcement  learning. SIAM Journal on Scientific Computing, 45(2), A579–A595. https://doi.org/10.1137/21M1412682
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[47]
2023 | Journal Article | LibreCat-ID: 46784 | OA
Wallscheid, O., Peitz, S., Stenner, J., Weber, D., Boshoff, S., Meyer, M., Chidananda, V., & Schweins, O. (2023). ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids. Journal of Open Source Software, 8(89), Article 5616. https://doi.org/10.21105/joss.05616
LibreCat | DOI | Download (ext.)
 
[46]
2023 | Conference Paper | LibreCat-ID: 46813 | OA
Wohlleben, M. C., Muth, L., Peitz, S., & Sextro, W. (2023). Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits. Proceedings in Applied Mathematics and Mechanics. https://doi.org/10.1002/pamm.202300039
LibreCat | DOI | Download (ext.)
 
[45]
2023 | Preprint | LibreCat-ID: 48502 | OA
Peitz, S., Hunstig, A., Rose, H., & Meier, T. (2023). Accelerating the analysis of optical quantum systems using the Koopman operator.
LibreCat | Download (ext.)
 
[44]
2023 | Preprint | LibreCat-ID: 51159 | OA
Amakor, A. C., Sonntag, K., & Peitz, S. (2023). A multiobjective continuation method to compute the regularization path of deep neural networks. In arXiv.
LibreCat | Download (ext.)
 
[43]
2023 | Preprint | LibreCat-ID: 51158 | OA
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2023). Error analysis of kernel EDMD for prediction and control in the Koopman  framework. In arXiv:2312.10460.
LibreCat | Download (ext.) | arXiv
 
[42]
2023 | Preprint | LibreCat-ID: 32447 | OA
Sonntag, K., & Peitz, S. (2023). Fast Convergence of Inertial Multiobjective Gradient-like Systems with Asymptotic Vanishing Damping. In arXiv:2307.00975.
LibreCat | Download (ext.) | arXiv
 
[41]
2023 | Preprint | LibreCat-ID: 46578 | OA
Bernreuther, M., Dellnitz, M., Gebken, B., Müller, G., Peitz, S., Sonntag, K., & Volkwein, S. (2023). Multiobjective Optimization of Non-Smooth PDE-Constrained Problems. In arXiv:2308.01113.
LibreCat | Download (ext.) | arXiv
 
[40]
2022 | Book Chapter | LibreCat-ID: 16296 | OA
Banholzer, S., Gebken, B., Dellnitz, M., Peitz, S., & Volkwein, S. (2022). ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation. In H. Michael, H. Roland, K. Christian, U. Michael, & U. Stefan (Eds.), Non-Smooth and Complementarity-Based Distributed Parameter Systems (pp. 43–76). Springer. https://doi.org/10.1007/978-3-030-79393-7_3
LibreCat | DOI | Download (ext.)
 
[39]
2022 | Book Chapter | LibreCat-ID: 30294
Peitz, S., Dellnitz, M., & Bannenberg, S. (2022). Efficient Virtual Design and Testing of Autonomous Vehicles. In H. G. Bock, K.-H. Küfer, P. Maas, A. Milde, & V. Schulz (Eds.), German Success Stories in Industrial Mathematics (Vol. 35). Springer International Publishing. https://doi.org/10.1007/978-3-030-81455-7_23
LibreCat | DOI
 
[38]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus, S., Nüske, F., & Peitz, S. (2022). Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical, 55(31), 314002. https://doi.org/10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[37]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier, M. B., & Peitz, S. (2022). Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. In arXiv:2208.12094.
LibreCat | Download (ext.) | arXiv
 
[36]
2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker, K., Gebken, B., & Peitz, S. (2022). On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7797–7808. https://doi.org/10.1109/TPAMI.2021.3114962
LibreCat | Files available | DOI | Download (ext.)
 
[35]
2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben, M. C., Bender, A., Peitz, S., & Sextro, W. (2022). Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction. In Machine Learning, Optimization, and Data Science. Springer International Publishing. https://doi.org/10.1007/978-3-030-95470-3_8
LibreCat | DOI | Download (ext.)
 
[34]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier, M. B., & Peitz, S. (2021). Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications, 26(2). https://doi.org/10.3390/mca26020031
LibreCat | DOI | Download (ext.)
 
[33]
2021 | Journal Article | LibreCat-ID: 16867 | OA
Gebken, B., & Peitz, S. (2021). An efficient descent method for locally Lipschitz multiobjective optimization problems. Journal of Optimization Theory and Applications, 188, 696–723. https://doi.org/10.1007/s10957-020-01803-w
LibreCat | DOI | Download (ext.)
 
[32]
2021 | Journal Article | LibreCat-ID: 16295 | OA
Gebken, B., & Peitz, S. (2021). Inverse multiobjective optimization: Inferring decision criteria from data. Journal of Global Optimization, 80, 3–29. https://doi.org/10.1007/s10898-020-00983-z
LibreCat | DOI | Download (ext.)
 
[31]
2021 | Journal Article | LibreCat-ID: 16294 | OA
Ober-Blöbaum, S., & Peitz, S. (2021). Explicit multiobjective model predictive control for nonlinear systems  with symmetries. International Journal of Robust and Nonlinear Control, 31(2), 380–403. https://doi.org/10.1002/rnc.5281
LibreCat | DOI | Download (ext.)
 
[30]
2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, K., Ober-Blöbaum, S., & Peitz, S. (2020). Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach. In O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, & K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation. Cham: Springer. https://doi.org/10.1007/978-3-030-51264-4_9
LibreCat | DOI
 
[29]
2020 | Journal Article | LibreCat-ID: 10596
Schütze, O., Cuate, O., Martín, A., Peitz, S., & Dellnitz, M. (2020). Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization, 52(5), 832–855. https://doi.org/10.1080/0305215x.2019.1617286
LibreCat | DOI
 
[28]
2020 | Journal Article | LibreCat-ID: 16288
Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte, C. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406. https://doi.org/10.1016/j.physd.2020.132416
LibreCat | DOI
 
[27]
2020 | Book Chapter | LibreCat-ID: 16289
Peitz, S., & Klus, S. (2020). Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator. In Lecture Notes in Control and Information Sciences (Vol. 484, pp. 257–282). Cham: Springer. https://doi.org/10.1007/978-3-030-35713-9_10
LibreCat | DOI
 
[26]
2020 | Journal Article | LibreCat-ID: 16290 | OA
Bieker, K., Peitz, S., Brunton, S. L., Kutz, J. N., & Dellnitz, M. (2020). Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics, 34, 577–591. https://doi.org/10.1007/s00162-020-00520-4
LibreCat | DOI | Download (ext.)
 
[25]
2020 | Journal Article | LibreCat-ID: 16309
Peitz, S., Otto, S. E., & Rowley, C. W. (2020). Data-Driven Model Predictive Control using Interpolated Koopman  Generators. SIAM Journal on Applied Dynamical Systems, 19(3), 2162–2193. https://doi.org/10.1137/20M1325678
LibreCat | DOI | Download (ext.)
 
[24]
2020 | Journal Article | LibreCat-ID: 16297
Hernández Castellanos, C. I., Ober-Blöbaum, S., & Peitz, S. (2020). Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty. International Journal of Robust and Nonlinear Control, 30(17), 7593–7618. https://doi.org/10.1002/rnc.5197
LibreCat | DOI
 
[23]
2019 | Journal Article | LibreCat-ID: 10593
Peitz, S., & Klus, S. (2019). Koopman operator-based model reduction for switched-system control of PDEs. Automatica, 106, 184–191. https://doi.org/10.1016/j.automatica.2019.05.016
LibreCat | DOI
 
[22]
2019 | Journal Article | LibreCat-ID: 10595
Gebken, B., Peitz, S., & Dellnitz, M. (2019). On the hierarchical structure of Pareto critical sets. Journal of Global Optimization, 73(4), 891–913. https://doi.org/10.1007/s10898-019-00737-6
LibreCat | DOI
 
[21]
2019 | Conference Paper | LibreCat-ID: 10597
Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., & Dellnitz, M. (2019). Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification. In 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE). https://doi.org/10.1109/precede.2019.8753313
LibreCat | DOI
 
[20]
2019 | Conference Paper | LibreCat-ID: 29636
Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., & Dellnitz, M. (2019). Finite-control-set model predictive control for a permanent magnet synchronous motor application with online least squares system identification. 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 1–6.
LibreCat
 
[19]
2018 | Preprint | LibreCat-ID: 21634 | OA
Hanke, S., Peitz, S., Wallscheid, O., Klus, S., Böcker, J., & Dellnitz, M. (2018). Koopman Operator-Based Finite-Control-Set Model Predictive Control for  Electrical Drives. ArXiv:1804.00854.
LibreCat | Download (ext.)
 
[18]
2018 | Book Chapter | LibreCat-ID: 22796
Kummert, F., Albers, A., Bremer, C., Büttner, S., Dellnitz, M., Dumitrescu, R., … Wittrowski, J. (2018). Eingesetzte wissenschaftliche Methoden. In A. Trächtler (Ed.), Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts. Paderborn: Springer.
LibreCat
 
[17]
2018 | Conference Paper | LibreCat-ID: 8750
Gebken, B., Peitz, S., & Dellnitz, M. (2018). A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems. In Numerical and Evolutionary Optimization – NEO 2017. Cham. https://doi.org/10.1007/978-3-319-96104-0_2
LibreCat | DOI
 
[16]
2018 | Journal Article | LibreCat-ID: 8751 | OA
Peitz, S., & Dellnitz, M. (2018). A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications, 23(2). https://doi.org/10.3390/mca23020030
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[15]
2018 | Book Chapter | LibreCat-ID: 8754
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition. In Reduced-Order Modeling (ROM) for Simulation and Optimization (pp. 47–72). Cham. https://doi.org/10.1007/978-3-319-75319-5_3
LibreCat | DOI
 
[14]
2018 | Journal Article | LibreCat-ID: 8755
Klus, S., Gelß, P., Peitz, S., & Schütte, C. (2018). Tensor-based dynamic mode decomposition. Nonlinearity, 31(7), 3359–3380. https://doi.org/10.1088/1361-6544/aabc8f
LibreCat | DOI
 
[13]
2018 | Conference Paper | LibreCat-ID: 8757
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). POD-based multiobjective optimal control of PDEs with non-smooth objectives. In PAMM (pp. 51–54). https://doi.org/10.1002/pamm.201710015
LibreCat | DOI
 
[12]
2018 | Preprint | LibreCat-ID: 16292 | OA
Peitz, S. (2018). Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data. ArXiv:1801.06419.
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[11]
2018 | Preprint | LibreCat-ID: 16293 | OA
Klus, S., Peitz, S., & Schuster, I. (2018). Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions. ArXiv:1805.10118.
LibreCat | Download (ext.)
 
[10]
2018 | Journal Article | LibreCat-ID: 29624
Hanke, S., Peitz, S., Wallscheid, O., Klus, S., Böcker, J., & Dellnitz, M. (2018). Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives. ArXiv Preprint ArXiv:1804.00854.
LibreCat
 
[9]
2018 | Journal Article | LibreCat-ID: 8753
Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2018). Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae Mathematicae, 161(1), 171–199. https://doi.org/10.1007/s10440-018-0209-7
LibreCat | DOI
 
[8]
2017 | Conference Paper | LibreCat-ID: 5914
Dellnitz, M., Eckstein, J., Flaßkamp, K., Friedel, P., Horenkamp, C., Köhler, U., … Tiemeyer, S. (2017). Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control. In Progress in Industrial Mathematics at ECMI 2014 (pp. 633–641). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-23413-7_87
LibreCat | DOI
 
[7]
2017 | Conference Paper | LibreCat-ID: 8752
Peitz, S., & Dellnitz, M. (2017). Gradient-Based Multiobjective Optimization with Uncertainties. In NEO 2016 (pp. 159–182). Cham. https://doi.org/10.1007/978-3-319-64063-1_7
LibreCat | DOI
 
[6]
2017 | Dissertation | LibreCat-ID: 10594 | OA
Peitz, S. (2017).   Exploiting structure in multiobjective optimization and optimal control. https://doi.org/10.17619/UNIPB/1-176
LibreCat | Files available | DOI | Download (ext.)
 
[5]
2017 | Journal Article | LibreCat-ID: 8756
Peitz, S., Schäfer, K., Ober-Blöbaum, S., Eckstein, J., Köhler, U., & Dellnitz, M. (2017). A multiobjective MPC approach for autonomously driven electric vehicles. Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC), 50(1), 8674–8679. https://doi.org/10.1016/j.ifacol.2017.08.1526
LibreCat | DOI
 
[4]
2016 | Conference Paper | LibreCat-ID: 8759
Peitz, S., Gräler, M., Henke, C., Molo, M. H., Dellnitz, M., & Trächtler, A. (2016). Multiobjective Model Predictive Control of an Industrial Laundry. In Procedia Technology (pp. 483–490). https://doi.org/10.1016/j.protcy.2016.08.061
LibreCat | DOI
 
[3]
2016 | Conference Paper | LibreCat-ID: 8758
Eckstein, J., Peitz, S., Schäfer, K., Friedel, P., Köhler, U., Hessel von Molo, M., Ober-Blöbaum, S., & Dellnitz, M. (2016). A comparison of two predictive approaches to control the longitudinal dynamics of electric vehicles. Procedia Technology, 3rd International Conference on System-Integrated Intelligence: New Challenges for Product and Production Engineering, 26, 465–472. https://doi.org/10.1016/j.protcy.2016.08.059
LibreCat | DOI
 
[2]
2016 | Conference Paper | LibreCat-ID: 29433
Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2016). Reduced order model based multiobjective optimal control of fluids. Proceedings of International Congress of Theoretical and Applied Mechanics.
LibreCat
 
[1]
2015 | Conference Paper | LibreCat-ID: 8760
Peitz, S., & Dellnitz, M. (2015). Multiobjective Optimization of the Flow Around a Cylinder Using Model Order Reduction. In PAMM (pp. 613–614). https://doi.org/10.1002/pamm.201510296
LibreCat | DOI
 
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61 Publications

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[61]
2024 | Preprint | LibreCat-ID: 51160 | OA
Philipp, F. M., Schaller, M., Boshoff, S., Peitz, S., Nüske, F., & Worthmann, K. (2024). Extended Dynamic Mode Decomposition: Sharp bounds on the sample  efficiency. In arXiv:2402.02494.
LibreCat | Download (ext.) | arXiv
 
[60]
2024 | Journal Article | LibreCat-ID: 46019 | OA
Sonntag, K., & Peitz, S. (2024). Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications. https://doi.org/10.1007/s10957-024-02389-3
LibreCat | DOI | Download (ext.)
 
[59]
2024 | Preprint | LibreCat-ID: 51334 | OA
Sonntag, K., Gebken, B., Müller, G., Peitz, S., & Volkwein, S. (2024). A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. In arXiv:2402.06376.
LibreCat | Download (ext.) | arXiv
 
[58]
2024 | Journal Article | LibreCat-ID: 40171 | OA
Peitz, S., Stenner, J., Chidananda, V., Wallscheid, O., Brunton, S. L., & Taira, K. (2024). Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning. Physica D: Nonlinear Phenomena, 461, 134096. https://doi.org/10.1016/j.physd.2024.134096
LibreCat | DOI | Download (ext.)
 
[57]
2024 | Journal Article | LibreCat-ID: 33461 | OA
Otto, S. E., Peitz, S., & Rowley, C. W. (2024). Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories. SIAM Journal on Applied Dynamical Systems, 23(1), 885–923. https://doi.org/10.1137/22M1523601
LibreCat | DOI | Download (ext.) | arXiv
 
[56]
2024 | Journal Article | LibreCat-ID: 38031 | OA
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2024). Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis , 71, Article 101657. https://doi.org/10.1016/j.acha.2024.101657
LibreCat | DOI | Download (ext.) | arXiv
 
[55]
2023 | Journal Article | LibreCat-ID: 21199 | OA
Peitz, S., & Bieker, K. (2023). On the Universal Transformation of Data-Driven Models to Control Systems. Automatica, 149, Article 110840. https://doi.org/10.1016/j.automatica.2022.110840
LibreCat | DOI | Download (ext.)
 
[54]
2023 | Preprint | LibreCat-ID: 42160 | OA
Werner, S., & Peitz, S. (2023). Learning a model is paramount for sample efficiency in reinforcement  learning control of PDEs. In arXiv:2302.07160.
LibreCat | Download (ext.) | arXiv
 
[53]
2023 | Journal Article | LibreCat-ID: 27426 | OA
Gebken, B., Bieker, K., & Peitz, S. (2023). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization, 85(3), 709–741. https://doi.org/10.1007/s10898-022-01223-2
LibreCat | DOI | Download (ext.)
 
[52]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller, M., Worthmann, K., Philipp, F., Peitz, S., & Nüske, F. (2023). Towards reliable data-based optimal and predictive control using extended DMD. IFAC-PapersOnLine, 56(1), 169–174. https://doi.org/10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[51]
2023 | Preprint | LibreCat-ID: 46579 | OA
Peitz, S., Harder, H., Nüske, F., Philipp, F., Schaller, M., & Worthmann, K. (2023). Partial observations, coarse graining and equivariance in Koopman  operator theory for large-scale dynamical systems. In arXiv:2307.15325.
LibreCat | Download (ext.) | arXiv
 
[50]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske, F., Peitz, S., Philipp, F., Schaller, M., & Worthmann, K. (2023). Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science, 33, Article 14. https://doi.org/10.1007/s00332-022-09862-1
LibreCat | DOI | Download (ext.)
 
[49]
2023 | Preprint | LibreCat-ID: 46649 | OA
Hotegni, S. S., Peitz, S., & Berkemeier, M. B. (2023). Multi-Objective Optimization for Sparse Deep Neural Network Training. In arXiv:2308.12243.
LibreCat | Download (ext.) | arXiv
 
[48]
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz, M., Hüllermeier, E., Lücke, M., Ober-Blöbaum, S., Offen, C., Peitz, S., & Pfannschmidt, K. (2023). Efficient time stepping for numerical integration using reinforcement  learning. SIAM Journal on Scientific Computing, 45(2), A579–A595. https://doi.org/10.1137/21M1412682
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[47]
2023 | Journal Article | LibreCat-ID: 46784 | OA
Wallscheid, O., Peitz, S., Stenner, J., Weber, D., Boshoff, S., Meyer, M., Chidananda, V., & Schweins, O. (2023). ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids. Journal of Open Source Software, 8(89), Article 5616. https://doi.org/10.21105/joss.05616
LibreCat | DOI | Download (ext.)
 
[46]
2023 | Conference Paper | LibreCat-ID: 46813 | OA
Wohlleben, M. C., Muth, L., Peitz, S., & Sextro, W. (2023). Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits. Proceedings in Applied Mathematics and Mechanics. https://doi.org/10.1002/pamm.202300039
LibreCat | DOI | Download (ext.)
 
[45]
2023 | Preprint | LibreCat-ID: 48502 | OA
Peitz, S., Hunstig, A., Rose, H., & Meier, T. (2023). Accelerating the analysis of optical quantum systems using the Koopman operator.
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[44]
2023 | Preprint | LibreCat-ID: 51159 | OA
Amakor, A. C., Sonntag, K., & Peitz, S. (2023). A multiobjective continuation method to compute the regularization path of deep neural networks. In arXiv.
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[43]
2023 | Preprint | LibreCat-ID: 51158 | OA
Philipp, F., Schaller, M., Worthmann, K., Peitz, S., & Nüske, F. (2023). Error analysis of kernel EDMD for prediction and control in the Koopman  framework. In arXiv:2312.10460.
LibreCat | Download (ext.) | arXiv
 
[42]
2023 | Preprint | LibreCat-ID: 32447 | OA
Sonntag, K., & Peitz, S. (2023). Fast Convergence of Inertial Multiobjective Gradient-like Systems with Asymptotic Vanishing Damping. In arXiv:2307.00975.
LibreCat | Download (ext.) | arXiv
 
[41]
2023 | Preprint | LibreCat-ID: 46578 | OA
Bernreuther, M., Dellnitz, M., Gebken, B., Müller, G., Peitz, S., Sonntag, K., & Volkwein, S. (2023). Multiobjective Optimization of Non-Smooth PDE-Constrained Problems. In arXiv:2308.01113.
LibreCat | Download (ext.) | arXiv
 
[40]
2022 | Book Chapter | LibreCat-ID: 16296 | OA
Banholzer, S., Gebken, B., Dellnitz, M., Peitz, S., & Volkwein, S. (2022). ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation. In H. Michael, H. Roland, K. Christian, U. Michael, & U. Stefan (Eds.), Non-Smooth and Complementarity-Based Distributed Parameter Systems (pp. 43–76). Springer. https://doi.org/10.1007/978-3-030-79393-7_3
LibreCat | DOI | Download (ext.)
 
[39]
2022 | Book Chapter | LibreCat-ID: 30294
Peitz, S., Dellnitz, M., & Bannenberg, S. (2022). Efficient Virtual Design and Testing of Autonomous Vehicles. In H. G. Bock, K.-H. Küfer, P. Maas, A. Milde, & V. Schulz (Eds.), German Success Stories in Industrial Mathematics (Vol. 35). Springer International Publishing. https://doi.org/10.1007/978-3-030-81455-7_23
LibreCat | DOI
 
[38]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus, S., Nüske, F., & Peitz, S. (2022). Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical, 55(31), 314002. https://doi.org/10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[37]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier, M. B., & Peitz, S. (2022). Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. In arXiv:2208.12094.
LibreCat | Download (ext.) | arXiv
 
[36]
2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker, K., Gebken, B., & Peitz, S. (2022). On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7797–7808. https://doi.org/10.1109/TPAMI.2021.3114962
LibreCat | Files available | DOI | Download (ext.)
 
[35]
2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben, M. C., Bender, A., Peitz, S., & Sextro, W. (2022). Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction. In Machine Learning, Optimization, and Data Science. Springer International Publishing. https://doi.org/10.1007/978-3-030-95470-3_8
LibreCat | DOI | Download (ext.)
 
[34]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier, M. B., & Peitz, S. (2021). Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications, 26(2). https://doi.org/10.3390/mca26020031
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[33]
2021 | Journal Article | LibreCat-ID: 16867 | OA
Gebken, B., & Peitz, S. (2021). An efficient descent method for locally Lipschitz multiobjective optimization problems. Journal of Optimization Theory and Applications, 188, 696–723. https://doi.org/10.1007/s10957-020-01803-w
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[32]
2021 | Journal Article | LibreCat-ID: 16295 | OA
Gebken, B., & Peitz, S. (2021). Inverse multiobjective optimization: Inferring decision criteria from data. Journal of Global Optimization, 80, 3–29. https://doi.org/10.1007/s10898-020-00983-z
LibreCat | DOI | Download (ext.)
 
[31]
2021 | Journal Article | LibreCat-ID: 16294 | OA
Ober-Blöbaum, S., & Peitz, S. (2021). Explicit multiobjective model predictive control for nonlinear systems  with symmetries. International Journal of Robust and Nonlinear Control, 31(2), 380–403. https://doi.org/10.1002/rnc.5281
LibreCat | DOI | Download (ext.)
 
[30]
2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, K., Ober-Blöbaum, S., & Peitz, S. (2020). Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach. In O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, & K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation. Cham: Springer. https://doi.org/10.1007/978-3-030-51264-4_9
LibreCat | DOI
 
[29]
2020 | Journal Article | LibreCat-ID: 10596
Schütze, O., Cuate, O., Martín, A., Peitz, S., & Dellnitz, M. (2020). Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization, 52(5), 832–855. https://doi.org/10.1080/0305215x.2019.1617286
LibreCat | DOI
 
[28]
2020 | Journal Article | LibreCat-ID: 16288
Klus, S., Nüske, F., Peitz, S., Niemann, J.-H., Clementi, C., & Schütte, C. (2020). Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena, 406. https://doi.org/10.1016/j.physd.2020.132416
LibreCat | DOI
 
[27]
2020 | Book Chapter | LibreCat-ID: 16289
Peitz, S., & Klus, S. (2020). Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator. In Lecture Notes in Control and Information Sciences (Vol. 484, pp. 257–282). Cham: Springer. https://doi.org/10.1007/978-3-030-35713-9_10
LibreCat | DOI
 
[26]
2020 | Journal Article | LibreCat-ID: 16290 | OA
Bieker, K., Peitz, S., Brunton, S. L., Kutz, J. N., & Dellnitz, M. (2020). Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics, 34, 577–591. https://doi.org/10.1007/s00162-020-00520-4
LibreCat | DOI | Download (ext.)
 
[25]
2020 | Journal Article | LibreCat-ID: 16309
Peitz, S., Otto, S. E., & Rowley, C. W. (2020). Data-Driven Model Predictive Control using Interpolated Koopman  Generators. SIAM Journal on Applied Dynamical Systems, 19(3), 2162–2193. https://doi.org/10.1137/20M1325678
LibreCat | DOI | Download (ext.)
 
[24]
2020 | Journal Article | LibreCat-ID: 16297
Hernández Castellanos, C. I., Ober-Blöbaum, S., & Peitz, S. (2020). Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty. International Journal of Robust and Nonlinear Control, 30(17), 7593–7618. https://doi.org/10.1002/rnc.5197
LibreCat | DOI
 
[23]
2019 | Journal Article | LibreCat-ID: 10593
Peitz, S., & Klus, S. (2019). Koopman operator-based model reduction for switched-system control of PDEs. Automatica, 106, 184–191. https://doi.org/10.1016/j.automatica.2019.05.016
LibreCat | DOI
 
[22]
2019 | Journal Article | LibreCat-ID: 10595
Gebken, B., Peitz, S., & Dellnitz, M. (2019). On the hierarchical structure of Pareto critical sets. Journal of Global Optimization, 73(4), 891–913. https://doi.org/10.1007/s10898-019-00737-6
LibreCat | DOI
 
[21]
2019 | Conference Paper | LibreCat-ID: 10597
Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., & Dellnitz, M. (2019). Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification. In 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE). https://doi.org/10.1109/precede.2019.8753313
LibreCat | DOI
 
[20]
2019 | Conference Paper | LibreCat-ID: 29636
Hanke, S., Peitz, S., Wallscheid, O., Böcker, J., & Dellnitz, M. (2019). Finite-control-set model predictive control for a permanent magnet synchronous motor application with online least squares system identification. 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics (PRECEDE), 1–6.
LibreCat
 
[19]
2018 | Preprint | LibreCat-ID: 21634 | OA
Hanke, S., Peitz, S., Wallscheid, O., Klus, S., Böcker, J., & Dellnitz, M. (2018). Koopman Operator-Based Finite-Control-Set Model Predictive Control for  Electrical Drives. ArXiv:1804.00854.
LibreCat | Download (ext.)
 
[18]
2018 | Book Chapter | LibreCat-ID: 22796
Kummert, F., Albers, A., Bremer, C., Büttner, S., Dellnitz, M., Dumitrescu, R., … Wittrowski, J. (2018). Eingesetzte wissenschaftliche Methoden. In A. Trächtler (Ed.), Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts. Paderborn: Springer.
LibreCat
 
[17]
2018 | Conference Paper | LibreCat-ID: 8750
Gebken, B., Peitz, S., & Dellnitz, M. (2018). A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems. In Numerical and Evolutionary Optimization – NEO 2017. Cham. https://doi.org/10.1007/978-3-319-96104-0_2
LibreCat | DOI
 
[16]
2018 | Journal Article | LibreCat-ID: 8751 | OA
Peitz, S., & Dellnitz, M. (2018). A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications, 23(2). https://doi.org/10.3390/mca23020030
LibreCat | DOI | Download (ext.)
 
[15]
2018 | Book Chapter | LibreCat-ID: 8754
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition. In Reduced-Order Modeling (ROM) for Simulation and Optimization (pp. 47–72). Cham. https://doi.org/10.1007/978-3-319-75319-5_3
LibreCat | DOI
 
[14]
2018 | Journal Article | LibreCat-ID: 8755
Klus, S., Gelß, P., Peitz, S., & Schütte, C. (2018). Tensor-based dynamic mode decomposition. Nonlinearity, 31(7), 3359–3380. https://doi.org/10.1088/1361-6544/aabc8f
LibreCat | DOI
 
[13]
2018 | Conference Paper | LibreCat-ID: 8757
Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). POD-based multiobjective optimal control of PDEs with non-smooth objectives. In PAMM (pp. 51–54). https://doi.org/10.1002/pamm.201710015
LibreCat | DOI
 
[12]
2018 | Preprint | LibreCat-ID: 16292 | OA
Peitz, S. (2018). Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data. ArXiv:1801.06419.
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[11]
2018 | Preprint | LibreCat-ID: 16293 | OA
Klus, S., Peitz, S., & Schuster, I. (2018). Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions. ArXiv:1805.10118.
LibreCat | Download (ext.)
 
[10]
2018 | Journal Article | LibreCat-ID: 29624
Hanke, S., Peitz, S., Wallscheid, O., Klus, S., Böcker, J., & Dellnitz, M. (2018). Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives. ArXiv Preprint ArXiv:1804.00854.
LibreCat
 
[9]
2018 | Journal Article | LibreCat-ID: 8753
Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2018). Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae Mathematicae, 161(1), 171–199. https://doi.org/10.1007/s10440-018-0209-7
LibreCat | DOI
 
[8]
2017 | Conference Paper | LibreCat-ID: 5914
Dellnitz, M., Eckstein, J., Flaßkamp, K., Friedel, P., Horenkamp, C., Köhler, U., … Tiemeyer, S. (2017). Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control. In Progress in Industrial Mathematics at ECMI 2014 (pp. 633–641). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-23413-7_87
LibreCat | DOI
 
[7]
2017 | Conference Paper | LibreCat-ID: 8752
Peitz, S., & Dellnitz, M. (2017). Gradient-Based Multiobjective Optimization with Uncertainties. In NEO 2016 (pp. 159–182). Cham. https://doi.org/10.1007/978-3-319-64063-1_7
LibreCat | DOI
 
[6]
2017 | Dissertation | LibreCat-ID: 10594 | OA
Peitz, S. (2017).   Exploiting structure in multiobjective optimization and optimal control. https://doi.org/10.17619/UNIPB/1-176
LibreCat | Files available | DOI | Download (ext.)
 
[5]
2017 | Journal Article | LibreCat-ID: 8756
Peitz, S., Schäfer, K., Ober-Blöbaum, S., Eckstein, J., Köhler, U., & Dellnitz, M. (2017). A multiobjective MPC approach for autonomously driven electric vehicles. Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC), 50(1), 8674–8679. https://doi.org/10.1016/j.ifacol.2017.08.1526
LibreCat | DOI
 
[4]
2016 | Conference Paper | LibreCat-ID: 8759
Peitz, S., Gräler, M., Henke, C., Molo, M. H., Dellnitz, M., & Trächtler, A. (2016). Multiobjective Model Predictive Control of an Industrial Laundry. In Procedia Technology (pp. 483–490). https://doi.org/10.1016/j.protcy.2016.08.061
LibreCat | DOI
 
[3]
2016 | Conference Paper | LibreCat-ID: 8758
Eckstein, J., Peitz, S., Schäfer, K., Friedel, P., Köhler, U., Hessel von Molo, M., Ober-Blöbaum, S., & Dellnitz, M. (2016). A comparison of two predictive approaches to control the longitudinal dynamics of electric vehicles. Procedia Technology, 3rd International Conference on System-Integrated Intelligence: New Challenges for Product and Production Engineering, 26, 465–472. https://doi.org/10.1016/j.protcy.2016.08.059
LibreCat | DOI
 
[2]
2016 | Conference Paper | LibreCat-ID: 29433
Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2016). Reduced order model based multiobjective optimal control of fluids. Proceedings of International Congress of Theoretical and Applied Mechanics.
LibreCat
 
[1]
2015 | Conference Paper | LibreCat-ID: 8760
Peitz, S., & Dellnitz, M. (2015). Multiobjective Optimization of the Flow Around a Cylinder Using Model Order Reduction. In PAMM (pp. 613–614). https://doi.org/10.1002/pamm.201510296
LibreCat | DOI
 
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