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64 Publications
2021 | Journal Article | LibreCat-ID: 21337 | 
Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models.” Mathematical and Computational Applications 26, no. 2 (2021). https://doi.org/10.3390/mca26020031.
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2021 | Journal Article | LibreCat-ID: 16867 |
Gebken, Bennet, and Sebastian Peitz. “An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems.” Journal of Optimization Theory and Applications 188 (2021): 696–723. https://doi.org/10.1007/s10957-020-01803-w.
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2021 | Journal Article | LibreCat-ID: 16295 |
Gebken, Bennet, and Sebastian Peitz. “Inverse Multiobjective Optimization: Inferring Decision Criteria from Data.” Journal of Global Optimization 80 (2021): 3–29. https://doi.org/10.1007/s10898-020-00983-z.
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2021 | Journal Article | LibreCat-ID: 16294 |
Ober-Blöbaum, Sina, and Sebastian Peitz. “Explicit Multiobjective Model Predictive Control for Nonlinear Systems with Symmetries.” International Journal of Robust and Nonlinear Control 31(2) (2021): 380–403. https://doi.org/10.1002/rnc.5281.
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2020 | Book Chapter | LibreCat-ID: 17411
Flaßkamp, Kathrin, Sina Ober-Blöbaum, and Sebastian Peitz. “Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach.” In Advances in Dynamics, Optimization and Computation, edited by Oliver Junge, Oliver Schütze, Gary Froyland, Sina Ober-Blöbaum, and Kathrin Padberg-Gehle. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-51264-4_9.
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2020 | Journal Article | LibreCat-ID: 10596
Schütze, Oliver, Oliver Cuate, Adanay Martín, Sebastian Peitz, and Michael Dellnitz. “Pareto Explorer: A Global/Local Exploration Tool for Many-Objective Optimization Problems.” Engineering Optimization 52, no. 5 (2020): 832–55. https://doi.org/10.1080/0305215x.2019.1617286.
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2020 | Journal Article | LibreCat-ID: 16288
Klus, Stefan, Feliks Nüske, Sebastian Peitz, Jan-Hendrik Niemann, Cecilia Clementi, and Christof Schütte. “Data-Driven Approximation of the Koopman Generator: Model Reduction, System Identification, and Control.” Physica D: Nonlinear Phenomena 406 (2020). https://doi.org/10.1016/j.physd.2020.132416.
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2020 | Book Chapter | LibreCat-ID: 16289
Peitz, Sebastian, and Stefan 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, 484:257–82. Lecture Notes in Control and Information Sciences. Cham: Springer, 2020. https://doi.org/10.1007/978-3-030-35713-9_10.
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2020 | Journal Article | LibreCat-ID: 16290 |
Bieker, Katharina, Sebastian Peitz, Steven L. Brunton, J. Nathan Kutz, and Michael Dellnitz. “Deep Model Predictive Flow Control with Limited Sensor Data and Online Learning.” Theoretical and Computational Fluid Dynamics 34 (2020): 577–591. https://doi.org/10.1007/s00162-020-00520-4.
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2020 | Journal Article | LibreCat-ID: 16309
Peitz, Sebastian, Samuel E. Otto, and Clarence W. Rowley. “Data-Driven Model Predictive Control Using Interpolated Koopman Generators.” SIAM Journal on Applied Dynamical Systems 19, no. 3 (2020): 2162–93. https://doi.org/10.1137/20M1325678.
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