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64 Publications
2021 | Journal Article | LibreCat-ID: 21337 |
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.
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2021 | Journal Article | LibreCat-ID: 16867 |
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.
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2021 | Journal Article | LibreCat-ID: 16295 |
B. Gebken and S. Peitz, “Inverse multiobjective optimization: Inferring decision criteria from data,” Journal of Global Optimization, vol. 80, pp. 3–29, 2021.
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2021 | Journal Article | LibreCat-ID: 16294 |
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.
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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.
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2020 | Journal Article | LibreCat-ID: 16290 |
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.
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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.
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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.
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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.
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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.
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2018 | Preprint | LibreCat-ID: 21634 |
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.
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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.
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2018 | Journal Article | LibreCat-ID: 8751 |
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.
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