Sebastian Peitz

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

61 Publications

Mark all

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

Mark all

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