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64 Publications
2021 | Journal Article | LibreCat-ID: 21337 | 
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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2021 | Journal Article | LibreCat-ID: 16867 |
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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2021 | Journal Article | LibreCat-ID: 16295 |
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
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2021 | Journal Article | LibreCat-ID: 16294 |
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
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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
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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
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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
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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
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2020 | Journal Article | LibreCat-ID: 16290 |
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
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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
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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
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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
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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
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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
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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.
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2018 | Preprint | LibreCat-ID: 21634 |
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.
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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.
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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
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2018 | Journal Article | LibreCat-ID: 8751 |
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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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
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