Sebastian Peitz

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

90 Publications

Mark all

[90]
2026 | Journal Article | LibreCat-ID: 51160 | OA
Philipp FM, Schaller M, Boshoff S, Peitz S, Nüske F, Worthmann K. Variance representations and convergence rates for data-driven approximations of Koopman operators. Physica D: Nonlinear Phenomena. 2026;492. doi:10.1016/j.physd.2026.135223
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[89]
2026 | Journal Article | LibreCat-ID: 53858 | OA
Akhter J, Fährmann PD, Sonntag K, Peitz S. Common pitfalls to avoid while using multiobjective optimization in machine learning. SIAM Review. 2026;68(3):656-683. doi:10.1137/24M1658875
LibreCat | DOI | Download (ext.)
 
[88]
2026 | Conference Paper | LibreCat-ID: 67308
Amakor AC, Berkemeier MB, Wohlleben MC, Sextro W, Peitz S. Surrogate-Assisted Multi-objective Design of Complex Multibody Systems. In: Senn W, Sanguineti M, Saudargiene A, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2025. Springer Nature Switzerland; 2026:251–262. doi:10.1007/978-3-032-04555-3_21
LibreCat | DOI
 
[87]
2026 | Conference Paper | LibreCat-ID: 67307 | OA
Hotegni SS, Peitz S. SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion. In: 14th International Conference on Learning Representations (ICLR). ; 2026. doi:10.48550/arXiv.2509.21058
LibreCat | DOI | Download (ext.)
 
[86]
2026 | Preprint | LibreCat-ID: 67306 | OA
Stenner J, Harder H, Peitz S. Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection. arXiv:260630238. Published online 2026.
LibreCat | Download (ext.)
 
[85]
2026 | Preprint | LibreCat-ID: 67309
Stenner J, Kilian A, Peitz S, de Meer H. Toward an Energy-Optimized Operation of Data Centers Located in Wind Farms Using Reinforcement Learning. arXiv:260630316. Published online 2026.
LibreCat
 
[84]
2026 | Conference Paper | LibreCat-ID: 67300
Hotegni SS, Peitz S. Enhancing Adversarial Robustness Through Multi-objective Representation Learning. In: Senn W, Sanguineti M, Saudargiene A, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2025. Springer Nature Switzerland; 2026:442–454. doi:10.1007/978-3-032-04558-4_35
LibreCat | DOI
 
[83]
2026 | Journal Article | LibreCat-ID: 67302
Markmann T, Straat M, Peitz S, Hammer B. Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection. Neurocomputing. 2026;679:133201. doi:10.1016/j.neucom.2026.133201
LibreCat | DOI
 
[82]
2026 | Conference Paper | LibreCat-ID: 67299 | OA
Harder H, Vishwasrao A, Guastoni L, Vinuesa R, Peitz S. Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In: Sukhatme G, Lindemann L, Tu S, Wierman A, Atanasov N, eds. Proceedings of The 8th Annual Learning for Dynamics and Control Conference. Vol 331. Proceedings of Machine Learning Research. PMLR; 2026:1601–1619. doi:10.48550/arXiv.2511.04641
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[81]
2026 | Conference Paper | LibreCat-ID: 67303 | OA
Amakor AC, Sonntag K, Peitz S. Interactive Pareto navigation for deep multi-task learning. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). ; 2026:652-668. doi:10.1007/978-3-032-37667-1_37
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[80]
2026 | Conference Paper | LibreCat-ID: 67305 | OA
Becktepe J, Franz A, Thuerey N, Peitz S. Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control. In: International Conference on Machine Learning (ICML). ; 2026. doi:10.48550/arXiv.2601.15015
LibreCat | DOI | Download (ext.)
 
[79]
2026 | Journal Article | LibreCat-ID: 67301
Wohlleben MC, Schütte J, Berkemeier M, Sextro W, Peitz S. Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings. Multibody System Dynamics. Published online 2026. doi:10.1007/s11044-026-10146-9
LibreCat | DOI
 
[78]
2026 | Preprint | LibreCat-ID: 67298 | OA
Mugisho Zagabe C, Peitz S. Automatic feature identification in least-squares policy iteration using the Koopman operator framework. arXiv:260326464. Published online 2026.
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[77]
2026 | Preprint | LibreCat-ID: 67304 | OA
Plotzki T, Peitz S. Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection. arXiv:260328074. Published online 2026.
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[76]
2025 | Journal Article | LibreCat-ID: 51159
Amakor AC, Sonntag K, Peitz S. A multiobjective continuation method to compute the regularization path of deep neural networks. Machine Learning with Applications. 2025;19. doi:10.1016/j.mlwa.2025.100625
LibreCat | Files available | DOI
 
[75]
2025 | Journal Article | LibreCat-ID: 46579 | OA
Peitz S, Harder H, Nüske F, Philipp F, Schaller M, Worthmann K. Equivariance and partial observations in Koopman operator theory for partial differential equations. Journal of Computational Dynamics. 2025;12:305-324. doi:10.3934/jcd.2024035
LibreCat | DOI | Download (ext.) | arXiv
 
[74]
2025 | Conference Paper | LibreCat-ID: 53793 | OA
Harder H, Peitz S. Solving partial differential equations with equivariant extreme learning machines. In: Berberich J, Ianelli A, Allgöwer F, eds. Systems Theory in Data and Optimization. Springer; 2025:153-168. doi:10.1007/978-3-031-83191-1_10
LibreCat | DOI | Download (ext.)
 
[73]
2025 | Conference Paper | LibreCat-ID: 67313
Voth D, Dane L, Grebe J, Peitz S, Terhörst P. Effective Backdoor Learning on Open-Set Face Recognition Systems. In: 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). ; 2025:1027-1039. doi:10.1109/WACV61041.2025.00109
LibreCat | DOI
 
[72]
2025 | Preprint | LibreCat-ID: 67312
Markmann T, Straat M, Peitz S, Hammer B. Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime. arXiv:250412000. Published online 2025.
LibreCat
 
[71]
2025 | Preprint | LibreCat-ID: 67310
Boshoff S, Peitz S, Klus S. Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces. arXiv:250922482. Published online 2025.
LibreCat
 
[70]
2025 | Journal Article | LibreCat-ID: 57829
de Payrebrune KM, Flaßkamp K, Ströhla T, et al. The impact of AI on engineering design procedures for dynamical systems. Technische Mechanik - European Journal of Engineering Mechanics. 2025;45(1):1-23. doi:10.24352/UB.OVGU-2025-037
LibreCat | DOI
 
[69]
2025 | Journal Article | LibreCat-ID: 51158 | OA
Philipp F, Schaller M, Worthmann K, Peitz S, Nüske F. Error analysis of kernel EDMD for prediction and control in the Koopman  framework. ournal of Nonlinear Science. 2025;35. doi:10.1007/s00332-025-10182-3
LibreCat | DOI | Download (ext.) | arXiv
 
[68]
2025 | Journal Article | LibreCat-ID: 67319
de Payrebrune KM, Flaßkamp K, Ströhla T, et al. The impact of AI on engineering design procedures for dynamical systems. Technische Mechanik - European Journal of Engineering Mechanics. 2025;45(1):1–23. doi:10.24352/UB.OVGU-2025-037
LibreCat | DOI
 
[67]
2025 | Journal Article | LibreCat-ID: 67317
Berkemeier M, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. Open Journal of Mathematical Optimization. 2025;6:1–36. doi:10.5802/ojmo.47
LibreCat | DOI
 
[66]
2025 | Journal Article | LibreCat-ID: 67314
Harder H, Peitz S, Nüske F, Philipp F, Schaller M, Worthmann K. Group Convolutional Extended Dynamic Mode Decomposition. Physica D: Nonlinear Phenomena. 2025;480:134725. doi:10.1016/j.physd.2025.134725
LibreCat | DOI
 
[65]
2025 | Journal Article | LibreCat-ID: 67316
Peitz S, Hotegni SS. Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art. Machine Learning with Applications. 2025;(100700). doi:10.1016/j.mlwa.2025.100700
LibreCat | DOI
 
[64]
2025 | Preprint | LibreCat-ID: 67315
Straat M, Markmann T, Peitz S, Hammer B. Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning. arXiv:251100272. Published online 2025.
LibreCat
 
[63]
2025 | Preprint | LibreCat-ID: 67318
Fromme F, Allen-Blanchette C, Harder H, Peitz S. Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders. arXiv:250513569. Published online 2025.
LibreCat
 
[62]
2024 | Journal Article | LibreCat-ID: 46019 | OA
Sonntag K, Peitz S. Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications. Published online 2024. doi:10.1007/s10957-024-02389-3
LibreCat | DOI | Download (ext.)
 
[61]
2024 | Journal Article | LibreCat-ID: 40171 | OA
Peitz S, Stenner J, Chidananda V, Wallscheid O, Brunton SL, Taira K. Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning. Physica D: Nonlinear Phenomena. 2024;461:134096. doi:10.1016/j.physd.2024.134096
LibreCat | DOI | Download (ext.)
 
[60]
2024 | Journal Article | LibreCat-ID: 33461 | OA
Otto SE, Peitz S, Rowley CW. Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories. SIAM Journal on Applied Dynamical Systems. 2024;23(1):885-923. doi:10.1137/22M1523601
LibreCat | DOI | Download (ext.) | arXiv
 
[59]
2024 | Journal Article | LibreCat-ID: 38031 | OA
Philipp F, Schaller M, Worthmann K, Peitz S, Nüske F. Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis . 2024;71. doi:10.1016/j.acha.2024.101657
LibreCat | DOI | Download (ext.) | arXiv
 
[58]
2024 | Journal Article | LibreCat-ID: 32447
Sonntag K, Peitz S. Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization. 2024;34(3):2259-2286. doi:10.1137/23M1588512
LibreCat | DOI
 
[57]
2024 | Conference Paper | LibreCat-ID: 46649 | OA
Hotegni SS, Berkemeier MB, Peitz S. Multi-Objective Optimization for Sparse Deep Multi-Task Learning. In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE; 2024:9. doi:10.1109/IJCNN60899.2024.10650994
LibreCat | DOI | Download (ext.)
 
[56]
2024 | Journal Article | LibreCat-ID: 51334 | OA
Sonntag K, Gebken B, Müller G, Peitz S, Volkwein S. A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. Journal of Optimization Theory and Applications. 2024;203:455-487. doi:10.1007/s10957-024-02520-4
LibreCat | DOI | Download (ext.) | arXiv
 
[55]
2024 | Conference Paper | LibreCat-ID: 62913
Hunstig A, Peitz S, Rose H, Meier T. Accelerating the analysis of optical quantum systems using the Koopman operator. In: IEEE 63rd Conference on Decision and Control (CDC). IEEE; 2024. doi:10.1109/cdc56724.2024.10886589
LibreCat | DOI
 
[54]
2024 | Conference Paper | LibreCat-ID: 52758
Harder H, Peitz S. On the continuity and smoothness of the value function in reinforcement learning and optimal control. In: IEEE 63rd Conference on Decision and Control (CDC). IEEE; 2024:1935-1940. doi:10.1109/CDC56724.2024.10886529
LibreCat | DOI
 
[53]
2024 | Book Chapter | LibreCat-ID: 46578 | OA
Bernreuther M, Dellnitz M, Gebken B, et al. Multiobjective Optimization of Non-Smooth PDE-Constrained Problems. In: DFG Priority Programme 1962. Birkhäuser; 2024.
LibreCat | Download (ext.) | arXiv
 
[52]
2024 | Conference Paper | LibreCat-ID: 42160 | OA
Werner S, Peitz S. Numerical evidence for sample efficiency of model-based over model-free reinforcement learning control of partial differential equations. In: European Control Conference (ECC). IEEE; 2024:2958-2964. doi:10.23919/ECC64448.2024.10590945
LibreCat | DOI | Download (ext.) | arXiv
 
[51]
2024 | Conference Paper | LibreCat-ID: 48502 | OA
Peitz S, Hunstig A, Rose H, Meier T. Accelerating the analysis of optical quantum systems using the Koopman operator. In: IEEE 63rd Conference on Decision and Control (CDC). ; 2024:7964-7969. doi:10.1109/CDC56724.2024.10886589
LibreCat | DOI | Download (ext.)
 
[50]
2024 | Preprint | LibreCat-ID: 67320
Berkemeier M, Sonntag K, Peitz S. New Nonlinear Conjugate Gradient Methods with Guaranteed Descent for Multi-Objective Optimization. Optimizaton Online. Published online 2024.
LibreCat
 
[49]
2023 | Journal Article | LibreCat-ID: 21199 | OA
Peitz S, Bieker K. On the Universal Transformation of Data-Driven Models to Control Systems. Automatica. 2023;149. doi:10.1016/j.automatica.2022.110840
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[48]
2023 | Conference Paper | LibreCat-ID: 54838
Boshoff S, Stenner J, Weber D, et al. Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches. In: IEEE Power and Energy Student Summit (PESS). VDE; 2023:124-129.
LibreCat | Download (ext.)
 
[47]
2023 | Conference Paper | LibreCat-ID: 54839
Meyer M, Weber D, Chidananda V, et al. ElectricGrid.jl – Automated modeling of decentralized electrical energy grids. In: IEEE Power and Energy Student Summit (PESS). VDE; 2023:112-117.
LibreCat | Download (ext.)
 
[46]
2023 | Journal Article | LibreCat-ID: 27426 | OA
Gebken B, Bieker K, Peitz S. On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization. 2023;85(3):709-741. doi:10.1007/s10898-022-01223-2
LibreCat | DOI | Download (ext.)
 
[45]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller M, Worthmann K, Philipp F, Peitz S, Nüske F. Towards reliable data-based optimal and predictive control using extended DMD. In: IFAC-PapersOnLine. Vol 56. ; 2023:169-174. doi:10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[44]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske F, Peitz S, Philipp F, Schaller M, Worthmann K. Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science. 2023;33. doi:10.1007/s00332-022-09862-1
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[43]
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz M, Hüllermeier E, Lücke M, et al. Efficient time stepping for numerical integration using reinforcement  learning. SIAM Journal on Scientific Computing. 2023;45(2):A579-A595. doi:10.1137/21M1412682
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[42]
2023 | Journal Article | LibreCat-ID: 46784 | OA
Wallscheid O, Peitz S, Stenner J, et al. ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids. Journal of Open Source Software. 2023;8(89). doi:10.21105/joss.05616
LibreCat | DOI | Download (ext.)
 
[41]
2023 | Conference Paper | LibreCat-ID: 46813 | OA
Wohlleben MC, Muth L, Peitz S, Sextro W. Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits. In: Proceedings in Applied Mathematics and Mechanics. Wiley; 2023. doi:10.1002/pamm.202300039
LibreCat | DOI | Download (ext.)
 
[40]
2022 | Book Chapter | LibreCat-ID: 16296 | OA
Banholzer S, Gebken B, Dellnitz M, Peitz S, Volkwein S. ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation. In: Michael H, Roland H, Christian K, Michael U, Stefan U, eds. Non-Smooth and Complementarity-Based Distributed Parameter Systems. Springer; 2022:43-76. doi: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. Efficient Virtual Design and Testing of Autonomous Vehicles. In: Bock HG, Küfer K-H, Maas P, Milde A, Schulz V, eds. German Success Stories in Industrial Mathematics. Vol 35. Mathematics in Industry. Springer International Publishing; 2022. doi:10.1007/978-3-030-81455-7_23
LibreCat | DOI
 
[38]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus S, Nüske F, Peitz S. Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical. 2022;55(31):314002. doi:10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[37]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. arXiv:220812094. Published online 2022.
LibreCat | Download (ext.) | arXiv
 
[36]
2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker K, Gebken B, Peitz S. On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022;44(11):7797-7808. doi:10.1109/TPAMI.2021.3114962
LibreCat | Files available | DOI | Download (ext.)
 
[35]
2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben MC, Bender A, Peitz S, Sextro W. Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction. In: Machine Learning, Optimization, and Data Science. Springer International Publishing; 2022. doi:10.1007/978-3-030-95470-3_8
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[34]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications. 2021;26(2). doi:10.3390/mca26020031
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[33]
2021 | Journal Article | LibreCat-ID: 16867 | OA
Gebken B, Peitz S. An efficient descent method for locally Lipschitz multiobjective optimization problems. Journal of Optimization Theory and Applications. 2021;188:696-723. doi:10.1007/s10957-020-01803-w
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[32]
2021 | Journal Article | LibreCat-ID: 16295 | OA
Gebken B, Peitz S. Inverse multiobjective optimization: Inferring decision criteria from data. Journal of Global Optimization. 2021;80:3-29. doi:10.1007/s10898-020-00983-z
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[31]
2021 | Journal Article | LibreCat-ID: 16294 | OA
Ober-Blöbaum S, Peitz S. Explicit multiobjective model predictive control for nonlinear systems  with symmetries. International Journal of Robust and Nonlinear Control. 2021;31(2):380-403. doi:10.1002/rnc.5281
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[30]
2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp K, Ober-Blöbaum S, Peitz S. Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach. In: Junge O, Schütze O, Froyland G, Ober-Blöbaum S, Padberg-Gehle K, eds. Advances in Dynamics, Optimization and Computation. Cham: Springer; 2020. doi: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. Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization. 2020;52(5):832-855. doi: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. Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena. 2020;406. doi:10.1016/j.physd.2020.132416
LibreCat | DOI
 
[27]
2020 | Book Chapter | LibreCat-ID: 16289
Peitz S, Klus S. 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. Lecture Notes in Control and Information Sciences. Cham: Springer; 2020:257-282. doi:10.1007/978-3-030-35713-9_10
LibreCat | DOI
 
[26]
2020 | Journal Article | LibreCat-ID: 16290 | OA
Bieker K, Peitz S, Brunton SL, Kutz JN, Dellnitz M. Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics. 2020;34:577–591. doi:10.1007/s00162-020-00520-4
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[25]
2020 | Journal Article | LibreCat-ID: 16309
Peitz S, Otto SE, Rowley CW. Data-Driven Model Predictive Control using Interpolated Koopman  Generators. SIAM Journal on Applied Dynamical Systems. 2020;19(3):2162-2193. doi:10.1137/20M1325678
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[24]
2020 | Journal Article | LibreCat-ID: 16297
Hernández Castellanos CI, Ober-Blöbaum S, Peitz S. Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty. International Journal of Robust and Nonlinear Control. 2020;30(17):7593-7618. doi:10.1002/rnc.5197
LibreCat | DOI
 
[23]
2019 | Journal Article | LibreCat-ID: 10593
Peitz S, Klus S. Koopman operator-based model reduction for switched-system control of PDEs. Automatica. 2019;106:184-191. doi:10.1016/j.automatica.2019.05.016
LibreCat | DOI
 
[22]
2019 | Journal Article | LibreCat-ID: 10595
Gebken B, Peitz S, Dellnitz M. On the hierarchical structure of Pareto critical sets. Journal of Global Optimization. 2019;73(4):891-913. doi: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. 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. doi:10.1109/precede.2019.8753313
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[20]
2019 | Conference Paper | LibreCat-ID: 29636
Hanke S, Peitz S, Wallscheid O, Böcker J, Dellnitz M. 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). ; 2019:1–6.
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[19]
2018 | Preprint | LibreCat-ID: 21634 | OA
Hanke S, Peitz S, Wallscheid O, Klus S, Böcker J, Dellnitz M. Koopman Operator-Based Finite-Control-Set Model Predictive Control for  Electrical Drives. arXiv:180400854. 2018.
LibreCat | Download (ext.)
 
[18]
2018 | Book Chapter | LibreCat-ID: 22796
Kummert F, Albers A, Bremer C, et al. Eingesetzte wissenschaftliche Methoden. In: Trächtler A, ed. Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts. Paderborn: Springer; 2018.
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[17]
2018 | Conference Paper | LibreCat-ID: 8750
Gebken B, Peitz S, Dellnitz M. A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems. In: Numerical and Evolutionary Optimization – NEO 2017. Cham; 2018. doi:10.1007/978-3-319-96104-0_2
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[16]
2018 | Journal Article | LibreCat-ID: 8751 | OA
Peitz S, Dellnitz M. A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications. 2018;23(2). doi:10.3390/mca23020030
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[15]
2018 | Book Chapter | LibreCat-ID: 8754
Beermann D, Dellnitz M, Peitz S, Volkwein S. Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition. In: Reduced-Order Modeling (ROM) for Simulation and Optimization. Cham; 2018:47-72. doi:10.1007/978-3-319-75319-5_3
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[14]
2018 | Journal Article | LibreCat-ID: 8755
Klus S, Gelß P, Peitz S, Schütte C. Tensor-based dynamic mode decomposition. Nonlinearity. 2018;31(7):3359-3380. doi:10.1088/1361-6544/aabc8f
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[13]
2018 | Conference Paper | LibreCat-ID: 8757
Beermann D, Dellnitz M, Peitz S, Volkwein S. POD-based multiobjective optimal control of PDEs with non-smooth objectives. In: PAMM. ; 2018:51-54. doi:10.1002/pamm.201710015
LibreCat | DOI
 
[12]
2018 | Preprint | LibreCat-ID: 16292 | OA
Peitz S. Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data. arXiv:180106419. 2018.
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[11]
2018 | Preprint | LibreCat-ID: 16293 | OA
Klus S, Peitz S, Schuster I. Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions. arXiv:180510118. 2018.
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[10]
2018 | Journal Article | LibreCat-ID: 29624
Hanke S, Peitz S, Wallscheid O, Klus S, Böcker J, Dellnitz M. Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives. arXiv preprint arXiv:180400854. Published online 2018.
LibreCat
 
[9]
2018 | Journal Article | LibreCat-ID: 8753
Peitz S, Ober-Blöbaum S, Dellnitz M. Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae Mathematicae. 2018;161(1):171–199. doi:10.1007/s10440-018-0209-7
LibreCat | DOI
 
[8]
2017 | Conference Paper | LibreCat-ID: 5914
Dellnitz M, Eckstein J, Flaßkamp K, et al. Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control. In: Progress in Industrial Mathematics at ECMI 2014 . Cham: Springer International Publishing; 2017:633-641. doi:10.1007/978-3-319-23413-7_87
LibreCat | DOI
 
[7]
2017 | Conference Paper | LibreCat-ID: 8752
Peitz S, Dellnitz M. Gradient-Based Multiobjective Optimization with Uncertainties. In: NEO 2016. Cham; 2017:159-182. doi:10.1007/978-3-319-64063-1_7
LibreCat | DOI
 
[6]
2017 | Dissertation | LibreCat-ID: 10594 | OA
Peitz S.   Exploiting Structure in Multiobjective Optimization and Optimal Control.; 2017. doi: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. A multiobjective MPC approach for autonomously driven electric vehicles. Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC). 2017;50(1):8674-8679. doi:10.1016/j.ifacol.2017.08.1526
LibreCat | DOI
 
[4]
2016 | Conference Paper | LibreCat-ID: 8759
Peitz S, Gräler M, Henke C, Molo MH, Dellnitz M, Trächtler A. Multiobjective Model Predictive Control of an Industrial Laundry. In: Procedia Technology. ; 2016:483-490. doi:10.1016/j.protcy.2016.08.061
LibreCat | DOI
 
[3]
2016 | Conference Paper | LibreCat-ID: 8758
Eckstein J, Peitz S, Schäfer K, 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. Vol 26. ; 2016:465-472. doi:10.1016/j.protcy.2016.08.059
LibreCat | DOI
 
[2]
2016 | Conference Paper | LibreCat-ID: 29433
Peitz S, Ober-Blöbaum S, Dellnitz M. Reduced order model based multiobjective optimal control of fluids. In: Proceedings of International Congress of Theoretical and Applied Mechanics. ; 2016.
LibreCat
 
[1]
2015 | Conference Paper | LibreCat-ID: 8760
Peitz S, Dellnitz M. Multiobjective Optimization of the Flow Around a Cylinder Using Model Order Reduction. In: PAMM. ; 2015:613-614. doi:10.1002/pamm.201510296
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[90]
2026 | Journal Article | LibreCat-ID: 51160 | OA
Philipp FM, Schaller M, Boshoff S, Peitz S, Nüske F, Worthmann K. Variance representations and convergence rates for data-driven approximations of Koopman operators. Physica D: Nonlinear Phenomena. 2026;492. doi:10.1016/j.physd.2026.135223
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[89]
2026 | Journal Article | LibreCat-ID: 53858 | OA
Akhter J, Fährmann PD, Sonntag K, Peitz S. Common pitfalls to avoid while using multiobjective optimization in machine learning. SIAM Review. 2026;68(3):656-683. doi:10.1137/24M1658875
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[88]
2026 | Conference Paper | LibreCat-ID: 67308
Amakor AC, Berkemeier MB, Wohlleben MC, Sextro W, Peitz S. Surrogate-Assisted Multi-objective Design of Complex Multibody Systems. In: Senn W, Sanguineti M, Saudargiene A, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2025. Springer Nature Switzerland; 2026:251–262. doi:10.1007/978-3-032-04555-3_21
LibreCat | DOI
 
[87]
2026 | Conference Paper | LibreCat-ID: 67307 | OA
Hotegni SS, Peitz S. SPREAD: Sampling-based Pareto front Refinement via Efficient Adaptive Diffusion. In: 14th International Conference on Learning Representations (ICLR). ; 2026. doi:10.48550/arXiv.2509.21058
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[86]
2026 | Preprint | LibreCat-ID: 67306 | OA
Stenner J, Harder H, Peitz S. Sparse Sensor Placement in Multi-Agent Reinforcement Learning Control of Rayleigh-Bénard Convection. arXiv:260630238. Published online 2026.
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[85]
2026 | Preprint | LibreCat-ID: 67309
Stenner J, Kilian A, Peitz S, de Meer H. Toward an Energy-Optimized Operation of Data Centers Located in Wind Farms Using Reinforcement Learning. arXiv:260630316. Published online 2026.
LibreCat
 
[84]
2026 | Conference Paper | LibreCat-ID: 67300
Hotegni SS, Peitz S. Enhancing Adversarial Robustness Through Multi-objective Representation Learning. In: Senn W, Sanguineti M, Saudargiene A, et al., eds. Artificial Neural Networks and Machine Learning – ICANN 2025. Springer Nature Switzerland; 2026:442–454. doi:10.1007/978-3-032-04558-4_35
LibreCat | DOI
 
[83]
2026 | Journal Article | LibreCat-ID: 67302
Markmann T, Straat M, Peitz S, Hammer B. Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh–Bénard convection. Neurocomputing. 2026;679:133201. doi:10.1016/j.neucom.2026.133201
LibreCat | DOI
 
[82]
2026 | Conference Paper | LibreCat-ID: 67299 | OA
Harder H, Vishwasrao A, Guastoni L, Vinuesa R, Peitz S. Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systems. In: Sukhatme G, Lindemann L, Tu S, Wierman A, Atanasov N, eds. Proceedings of The 8th Annual Learning for Dynamics and Control Conference. Vol 331. Proceedings of Machine Learning Research. PMLR; 2026:1601–1619. doi:10.48550/arXiv.2511.04641
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[81]
2026 | Conference Paper | LibreCat-ID: 67303 | OA
Amakor AC, Sonntag K, Peitz S. Interactive Pareto navigation for deep multi-task learning. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). ; 2026:652-668. doi:10.1007/978-3-032-37667-1_37
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[80]
2026 | Conference Paper | LibreCat-ID: 67305 | OA
Becktepe J, Franz A, Thuerey N, Peitz S. Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control. In: International Conference on Machine Learning (ICML). ; 2026. doi:10.48550/arXiv.2601.15015
LibreCat | DOI | Download (ext.)
 
[79]
2026 | Journal Article | LibreCat-ID: 67301
Wohlleben MC, Schütte J, Berkemeier M, Sextro W, Peitz S. Evaluating Physics-Based, Hybrid, and Data-Driven Models for Rubber-Metal Bushings. Multibody System Dynamics. Published online 2026. doi:10.1007/s11044-026-10146-9
LibreCat | DOI
 
[78]
2026 | Preprint | LibreCat-ID: 67298 | OA
Mugisho Zagabe C, Peitz S. Automatic feature identification in least-squares policy iteration using the Koopman operator framework. arXiv:260326464. Published online 2026.
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[77]
2026 | Preprint | LibreCat-ID: 67304 | OA
Plotzki T, Peitz S. Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection. arXiv:260328074. Published online 2026.
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[76]
2025 | Journal Article | LibreCat-ID: 51159
Amakor AC, Sonntag K, Peitz S. A multiobjective continuation method to compute the regularization path of deep neural networks. Machine Learning with Applications. 2025;19. doi:10.1016/j.mlwa.2025.100625
LibreCat | Files available | DOI
 
[75]
2025 | Journal Article | LibreCat-ID: 46579 | OA
Peitz S, Harder H, Nüske F, Philipp F, Schaller M, Worthmann K. Equivariance and partial observations in Koopman operator theory for partial differential equations. Journal of Computational Dynamics. 2025;12:305-324. doi:10.3934/jcd.2024035
LibreCat | DOI | Download (ext.) | arXiv
 
[74]
2025 | Conference Paper | LibreCat-ID: 53793 | OA
Harder H, Peitz S. Solving partial differential equations with equivariant extreme learning machines. In: Berberich J, Ianelli A, Allgöwer F, eds. Systems Theory in Data and Optimization. Springer; 2025:153-168. doi:10.1007/978-3-031-83191-1_10
LibreCat | DOI | Download (ext.)
 
[73]
2025 | Conference Paper | LibreCat-ID: 67313
Voth D, Dane L, Grebe J, Peitz S, Terhörst P. Effective Backdoor Learning on Open-Set Face Recognition Systems. In: 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). ; 2025:1027-1039. doi:10.1109/WACV61041.2025.00109
LibreCat | DOI
 
[72]
2025 | Preprint | LibreCat-ID: 67312
Markmann T, Straat M, Peitz S, Hammer B. Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime. arXiv:250412000. Published online 2025.
LibreCat
 
[71]
2025 | Preprint | LibreCat-ID: 67310
Boshoff S, Peitz S, Klus S. Bayesian Transfer Operators in Reproducing Kernel Hilbert Spaces. arXiv:250922482. Published online 2025.
LibreCat
 
[70]
2025 | Journal Article | LibreCat-ID: 57829
de Payrebrune KM, Flaßkamp K, Ströhla T, et al. The impact of AI on engineering design procedures for dynamical systems. Technische Mechanik - European Journal of Engineering Mechanics. 2025;45(1):1-23. doi:10.24352/UB.OVGU-2025-037
LibreCat | DOI
 
[69]
2025 | Journal Article | LibreCat-ID: 51158 | OA
Philipp F, Schaller M, Worthmann K, Peitz S, Nüske F. Error analysis of kernel EDMD for prediction and control in the Koopman  framework. ournal of Nonlinear Science. 2025;35. doi:10.1007/s00332-025-10182-3
LibreCat | DOI | Download (ext.) | arXiv
 
[68]
2025 | Journal Article | LibreCat-ID: 67319
de Payrebrune KM, Flaßkamp K, Ströhla T, et al. The impact of AI on engineering design procedures for dynamical systems. Technische Mechanik - European Journal of Engineering Mechanics. 2025;45(1):1–23. doi:10.24352/UB.OVGU-2025-037
LibreCat | DOI
 
[67]
2025 | Journal Article | LibreCat-ID: 67317
Berkemeier M, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. Open Journal of Mathematical Optimization. 2025;6:1–36. doi:10.5802/ojmo.47
LibreCat | DOI
 
[66]
2025 | Journal Article | LibreCat-ID: 67314
Harder H, Peitz S, Nüske F, Philipp F, Schaller M, Worthmann K. Group Convolutional Extended Dynamic Mode Decomposition. Physica D: Nonlinear Phenomena. 2025;480:134725. doi:10.1016/j.physd.2025.134725
LibreCat | DOI
 
[65]
2025 | Journal Article | LibreCat-ID: 67316
Peitz S, Hotegni SS. Multi-objective Deep Learning: Taxonomy and Survey of the State of the Art. Machine Learning with Applications. 2025;(100700). doi:10.1016/j.mlwa.2025.100700
LibreCat | DOI
 
[64]
2025 | Preprint | LibreCat-ID: 67315
Straat M, Markmann T, Peitz S, Hammer B. Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning. arXiv:251100272. Published online 2025.
LibreCat
 
[63]
2025 | Preprint | LibreCat-ID: 67318
Fromme F, Allen-Blanchette C, Harder H, Peitz S. Surrogate Modeling of 3D Rayleigh-Bénard Convection with Equivariant Autoencoders. arXiv:250513569. Published online 2025.
LibreCat
 
[62]
2024 | Journal Article | LibreCat-ID: 46019 | OA
Sonntag K, Peitz S. Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems. Journal of Optimization Theory and Applications. Published online 2024. doi:10.1007/s10957-024-02389-3
LibreCat | DOI | Download (ext.)
 
[61]
2024 | Journal Article | LibreCat-ID: 40171 | OA
Peitz S, Stenner J, Chidananda V, Wallscheid O, Brunton SL, Taira K. Distributed Control of Partial Differential Equations Using  Convolutional Reinforcement Learning. Physica D: Nonlinear Phenomena. 2024;461:134096. doi:10.1016/j.physd.2024.134096
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[60]
2024 | Journal Article | LibreCat-ID: 33461 | OA
Otto SE, Peitz S, Rowley CW. Learning Bilinear Models of Actuated Koopman Generators from  Partially-Observed Trajectories. SIAM Journal on Applied Dynamical Systems. 2024;23(1):885-923. doi:10.1137/22M1523601
LibreCat | DOI | Download (ext.) | arXiv
 
[59]
2024 | Journal Article | LibreCat-ID: 38031 | OA
Philipp F, Schaller M, Worthmann K, Peitz S, Nüske F. Error bounds for kernel-based approximations of the Koopman operator. Applied and Computational Harmonic Analysis . 2024;71. doi:10.1016/j.acha.2024.101657
LibreCat | DOI | Download (ext.) | arXiv
 
[58]
2024 | Journal Article | LibreCat-ID: 32447
Sonntag K, Peitz S. Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization. 2024;34(3):2259-2286. doi:10.1137/23M1588512
LibreCat | DOI
 
[57]
2024 | Conference Paper | LibreCat-ID: 46649 | OA
Hotegni SS, Berkemeier MB, Peitz S. Multi-Objective Optimization for Sparse Deep Multi-Task Learning. In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE; 2024:9. doi:10.1109/IJCNN60899.2024.10650994
LibreCat | DOI | Download (ext.)
 
[56]
2024 | Journal Article | LibreCat-ID: 51334 | OA
Sonntag K, Gebken B, Müller G, Peitz S, Volkwein S. A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces. Journal of Optimization Theory and Applications. 2024;203:455-487. doi:10.1007/s10957-024-02520-4
LibreCat | DOI | Download (ext.) | arXiv
 
[55]
2024 | Conference Paper | LibreCat-ID: 62913
Hunstig A, Peitz S, Rose H, Meier T. Accelerating the analysis of optical quantum systems using the Koopman operator. In: IEEE 63rd Conference on Decision and Control (CDC). IEEE; 2024. doi:10.1109/cdc56724.2024.10886589
LibreCat | DOI
 
[54]
2024 | Conference Paper | LibreCat-ID: 52758
Harder H, Peitz S. On the continuity and smoothness of the value function in reinforcement learning and optimal control. In: IEEE 63rd Conference on Decision and Control (CDC). IEEE; 2024:1935-1940. doi:10.1109/CDC56724.2024.10886529
LibreCat | DOI
 
[53]
2024 | Book Chapter | LibreCat-ID: 46578 | OA
Bernreuther M, Dellnitz M, Gebken B, et al. Multiobjective Optimization of Non-Smooth PDE-Constrained Problems. In: DFG Priority Programme 1962. Birkhäuser; 2024.
LibreCat | Download (ext.) | arXiv
 
[52]
2024 | Conference Paper | LibreCat-ID: 42160 | OA
Werner S, Peitz S. Numerical evidence for sample efficiency of model-based over model-free reinforcement learning control of partial differential equations. In: European Control Conference (ECC). IEEE; 2024:2958-2964. doi:10.23919/ECC64448.2024.10590945
LibreCat | DOI | Download (ext.) | arXiv
 
[51]
2024 | Conference Paper | LibreCat-ID: 48502 | OA
Peitz S, Hunstig A, Rose H, Meier T. Accelerating the analysis of optical quantum systems using the Koopman operator. In: IEEE 63rd Conference on Decision and Control (CDC). ; 2024:7964-7969. doi:10.1109/CDC56724.2024.10886589
LibreCat | DOI | Download (ext.)
 
[50]
2024 | Preprint | LibreCat-ID: 67320
Berkemeier M, Sonntag K, Peitz S. New Nonlinear Conjugate Gradient Methods with Guaranteed Descent for Multi-Objective Optimization. Optimizaton Online. Published online 2024.
LibreCat
 
[49]
2023 | Journal Article | LibreCat-ID: 21199 | OA
Peitz S, Bieker K. On the Universal Transformation of Data-Driven Models to Control Systems. Automatica. 2023;149. doi:10.1016/j.automatica.2022.110840
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[48]
2023 | Conference Paper | LibreCat-ID: 54838
Boshoff S, Stenner J, Weber D, et al. Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches. In: IEEE Power and Energy Student Summit (PESS). VDE; 2023:124-129.
LibreCat | Download (ext.)
 
[47]
2023 | Conference Paper | LibreCat-ID: 54839
Meyer M, Weber D, Chidananda V, et al. ElectricGrid.jl – Automated modeling of decentralized electrical energy grids. In: IEEE Power and Energy Student Summit (PESS). VDE; 2023:112-117.
LibreCat | Download (ext.)
 
[46]
2023 | Journal Article | LibreCat-ID: 27426 | OA
Gebken B, Bieker K, Peitz S. On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization. 2023;85(3):709-741. doi:10.1007/s10898-022-01223-2
LibreCat | DOI | Download (ext.)
 
[45]
2023 | Conference Paper | LibreCat-ID: 30125 | OA
Schaller M, Worthmann K, Philipp F, Peitz S, Nüske F. Towards reliable data-based optimal and predictive control using extended DMD. In: IFAC-PapersOnLine. Vol 56. ; 2023:169-174. doi:10.1016/j.ifacol.2023.02.029
LibreCat | DOI | Download (ext.) | arXiv
 
[44]
2023 | Journal Article | LibreCat-ID: 23428 | OA
Nüske F, Peitz S, Philipp F, Schaller M, Worthmann K. Finite-data error bounds for Koopman-based prediction and control. Journal of Nonlinear Science. 2023;33. doi:10.1007/s00332-022-09862-1
LibreCat | DOI | Download (ext.)
 
[43]
2023 | Journal Article | LibreCat-ID: 21600
Dellnitz M, Hüllermeier E, Lücke M, et al. Efficient time stepping for numerical integration using reinforcement  learning. SIAM Journal on Scientific Computing. 2023;45(2):A579-A595. doi:10.1137/21M1412682
LibreCat | Files available | DOI | Download (ext.) | arXiv
 
[42]
2023 | Journal Article | LibreCat-ID: 46784 | OA
Wallscheid O, Peitz S, Stenner J, et al. ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids. Journal of Open Source Software. 2023;8(89). doi:10.21105/joss.05616
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[41]
2023 | Conference Paper | LibreCat-ID: 46813 | OA
Wohlleben MC, Muth L, Peitz S, Sextro W. Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits. In: Proceedings in Applied Mathematics and Mechanics. Wiley; 2023. doi:10.1002/pamm.202300039
LibreCat | DOI | Download (ext.)
 
[40]
2022 | Book Chapter | LibreCat-ID: 16296 | OA
Banholzer S, Gebken B, Dellnitz M, Peitz S, Volkwein S. ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation. In: Michael H, Roland H, Christian K, Michael U, Stefan U, eds. Non-Smooth and Complementarity-Based Distributed Parameter Systems. Springer; 2022:43-76. doi:10.1007/978-3-030-79393-7_3
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[39]
2022 | Book Chapter | LibreCat-ID: 30294
Peitz S, Dellnitz M, Bannenberg S. Efficient Virtual Design and Testing of Autonomous Vehicles. In: Bock HG, Küfer K-H, Maas P, Milde A, Schulz V, eds. German Success Stories in Industrial Mathematics. Vol 35. Mathematics in Industry. Springer International Publishing; 2022. doi:10.1007/978-3-030-81455-7_23
LibreCat | DOI
 
[38]
2022 | Journal Article | LibreCat-ID: 29673 | OA
Klus S, Nüske F, Peitz S. Koopman analysis of quantum systems. Journal of Physics A: Mathematical and Theoretical. 2022;55(31):314002. doi:10.1088/1751-8121/ac7d22
LibreCat | DOI | Download (ext.) | arXiv
 
[37]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. arXiv:220812094. Published online 2022.
LibreCat | Download (ext.) | arXiv
 
[36]
2022 | Journal Article | LibreCat-ID: 20731 | OA
Bieker K, Gebken B, Peitz S. On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022;44(11):7797-7808. doi:10.1109/TPAMI.2021.3114962
LibreCat | Files available | DOI | Download (ext.)
 
[35]
2022 | Book Chapter | LibreCat-ID: 29727
Wohlleben MC, Bender A, Peitz S, Sextro W. Development of a Hybrid Modeling Methodology for Oscillating Systems with Friction. In: Machine Learning, Optimization, and Data Science. Springer International Publishing; 2022. doi:10.1007/978-3-030-95470-3_8
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[34]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications. 2021;26(2). doi:10.3390/mca26020031
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[33]
2021 | Journal Article | LibreCat-ID: 16867 | OA
Gebken B, Peitz S. An efficient descent method for locally Lipschitz multiobjective optimization problems. Journal of Optimization Theory and Applications. 2021;188:696-723. doi:10.1007/s10957-020-01803-w
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[32]
2021 | Journal Article | LibreCat-ID: 16295 | OA
Gebken B, Peitz S. Inverse multiobjective optimization: Inferring decision criteria from data. Journal of Global Optimization. 2021;80:3-29. doi:10.1007/s10898-020-00983-z
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[31]
2021 | Journal Article | LibreCat-ID: 16294 | OA
Ober-Blöbaum S, Peitz S. Explicit multiobjective model predictive control for nonlinear systems  with symmetries. International Journal of Robust and Nonlinear Control. 2021;31(2):380-403. doi:10.1002/rnc.5281
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[30]
2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp K, Ober-Blöbaum S, Peitz S. Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach. In: Junge O, Schütze O, Froyland G, Ober-Blöbaum S, Padberg-Gehle K, eds. Advances in Dynamics, Optimization and Computation. Cham: Springer; 2020. doi: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. Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization. 2020;52(5):832-855. doi: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. Data-driven approximation of the Koopman generator: Model reduction, system identification, and control. Physica D: Nonlinear Phenomena. 2020;406. doi:10.1016/j.physd.2020.132416
LibreCat | DOI
 
[27]
2020 | Book Chapter | LibreCat-ID: 16289
Peitz S, Klus S. 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. Lecture Notes in Control and Information Sciences. Cham: Springer; 2020:257-282. doi:10.1007/978-3-030-35713-9_10
LibreCat | DOI
 
[26]
2020 | Journal Article | LibreCat-ID: 16290 | OA
Bieker K, Peitz S, Brunton SL, Kutz JN, Dellnitz M. Deep model predictive flow control with limited sensor data and online learning. Theoretical and Computational Fluid Dynamics. 2020;34:577–591. doi:10.1007/s00162-020-00520-4
LibreCat | DOI | Download (ext.)
 
[25]
2020 | Journal Article | LibreCat-ID: 16309
Peitz S, Otto SE, Rowley CW. Data-Driven Model Predictive Control using Interpolated Koopman  Generators. SIAM Journal on Applied Dynamical Systems. 2020;19(3):2162-2193. doi:10.1137/20M1325678
LibreCat | DOI | Download (ext.)
 
[24]
2020 | Journal Article | LibreCat-ID: 16297
Hernández Castellanos CI, Ober-Blöbaum S, Peitz S. Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty. International Journal of Robust and Nonlinear Control. 2020;30(17):7593-7618. doi:10.1002/rnc.5197
LibreCat | DOI
 
[23]
2019 | Journal Article | LibreCat-ID: 10593
Peitz S, Klus S. Koopman operator-based model reduction for switched-system control of PDEs. Automatica. 2019;106:184-191. doi:10.1016/j.automatica.2019.05.016
LibreCat | DOI
 
[22]
2019 | Journal Article | LibreCat-ID: 10595
Gebken B, Peitz S, Dellnitz M. On the hierarchical structure of Pareto critical sets. Journal of Global Optimization. 2019;73(4):891-913. doi: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. 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. doi:10.1109/precede.2019.8753313
LibreCat | DOI
 
[20]
2019 | Conference Paper | LibreCat-ID: 29636
Hanke S, Peitz S, Wallscheid O, Böcker J, Dellnitz M. 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). ; 2019:1–6.
LibreCat
 
[19]
2018 | Preprint | LibreCat-ID: 21634 | OA
Hanke S, Peitz S, Wallscheid O, Klus S, Böcker J, Dellnitz M. Koopman Operator-Based Finite-Control-Set Model Predictive Control for  Electrical Drives. arXiv:180400854. 2018.
LibreCat | Download (ext.)
 
[18]
2018 | Book Chapter | LibreCat-ID: 22796
Kummert F, Albers A, Bremer C, et al. Eingesetzte wissenschaftliche Methoden. In: Trächtler A, ed. Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts. Paderborn: Springer; 2018.
LibreCat
 
[17]
2018 | Conference Paper | LibreCat-ID: 8750
Gebken B, Peitz S, Dellnitz M. A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems. In: Numerical and Evolutionary Optimization – NEO 2017. Cham; 2018. doi:10.1007/978-3-319-96104-0_2
LibreCat | DOI
 
[16]
2018 | Journal Article | LibreCat-ID: 8751 | OA
Peitz S, Dellnitz M. A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical and Computational Applications. 2018;23(2). doi:10.3390/mca23020030
LibreCat | DOI | Download (ext.)
 
[15]
2018 | Book Chapter | LibreCat-ID: 8754
Beermann D, Dellnitz M, Peitz S, Volkwein S. Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition. In: Reduced-Order Modeling (ROM) for Simulation and Optimization. Cham; 2018:47-72. doi: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. Tensor-based dynamic mode decomposition. Nonlinearity. 2018;31(7):3359-3380. doi:10.1088/1361-6544/aabc8f
LibreCat | DOI
 
[13]
2018 | Conference Paper | LibreCat-ID: 8757
Beermann D, Dellnitz M, Peitz S, Volkwein S. POD-based multiobjective optimal control of PDEs with non-smooth objectives. In: PAMM. ; 2018:51-54. doi:10.1002/pamm.201710015
LibreCat | DOI
 
[12]
2018 | Preprint | LibreCat-ID: 16292 | OA
Peitz S. Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data. arXiv:180106419. 2018.
LibreCat | Download (ext.)
 
[11]
2018 | Preprint | LibreCat-ID: 16293 | OA
Klus S, Peitz S, Schuster I. Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions. arXiv:180510118. 2018.
LibreCat | Download (ext.)
 
[10]
2018 | Journal Article | LibreCat-ID: 29624
Hanke S, Peitz S, Wallscheid O, Klus S, Böcker J, Dellnitz M. Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives. arXiv preprint arXiv:180400854. Published online 2018.
LibreCat
 
[9]
2018 | Journal Article | LibreCat-ID: 8753
Peitz S, Ober-Blöbaum S, Dellnitz M. Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae Mathematicae. 2018;161(1):171–199. doi:10.1007/s10440-018-0209-7
LibreCat | DOI
 
[8]
2017 | Conference Paper | LibreCat-ID: 5914
Dellnitz M, Eckstein J, Flaßkamp K, et al. Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control. In: Progress in Industrial Mathematics at ECMI 2014 . Cham: Springer International Publishing; 2017:633-641. doi:10.1007/978-3-319-23413-7_87
LibreCat | DOI
 
[7]
2017 | Conference Paper | LibreCat-ID: 8752
Peitz S, Dellnitz M. Gradient-Based Multiobjective Optimization with Uncertainties. In: NEO 2016. Cham; 2017:159-182. doi:10.1007/978-3-319-64063-1_7
LibreCat | DOI
 
[6]
2017 | Dissertation | LibreCat-ID: 10594 | OA
Peitz S.   Exploiting Structure in Multiobjective Optimization and Optimal Control.; 2017. doi: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. A multiobjective MPC approach for autonomously driven electric vehicles. Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC). 2017;50(1):8674-8679. doi:10.1016/j.ifacol.2017.08.1526
LibreCat | DOI
 
[4]
2016 | Conference Paper | LibreCat-ID: 8759
Peitz S, Gräler M, Henke C, Molo MH, Dellnitz M, Trächtler A. Multiobjective Model Predictive Control of an Industrial Laundry. In: Procedia Technology. ; 2016:483-490. doi:10.1016/j.protcy.2016.08.061
LibreCat | DOI
 
[3]
2016 | Conference Paper | LibreCat-ID: 8758
Eckstein J, Peitz S, Schäfer K, 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. Vol 26. ; 2016:465-472. doi:10.1016/j.protcy.2016.08.059
LibreCat | DOI
 
[2]
2016 | Conference Paper | LibreCat-ID: 29433
Peitz S, Ober-Blöbaum S, Dellnitz M. Reduced order model based multiobjective optimal control of fluids. In: Proceedings of International Congress of Theoretical and Applied Mechanics. ; 2016.
LibreCat
 
[1]
2015 | Conference Paper | LibreCat-ID: 8760
Peitz S, Dellnitz M. Multiobjective Optimization of the Flow Around a Cylinder Using Model Order Reduction. In: PAMM. ; 2015:613-614. doi:10.1002/pamm.201510296
LibreCat | DOI
 
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