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64 Publications


2021 | Journal Article | LibreCat-ID: 21337 | OA
Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models
M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).
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2021 | Journal Article | LibreCat-ID: 16867 | OA
An efficient descent method for locally Lipschitz multiobjective optimization problems
B. Gebken, S. Peitz, Journal of Optimization Theory and Applications 188 (2021) 696–723.
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2021 | Journal Article | LibreCat-ID: 16295 | OA
Inverse multiobjective optimization: Inferring decision criteria from data
B. Gebken, S. Peitz, Journal of Global Optimization 80 (2021) 3–29.
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2021 | Journal Article | LibreCat-ID: 16294 | OA
Explicit multiobjective model predictive control for nonlinear systems with symmetries
S. Ober-Blöbaum, S. Peitz, International Journal of Robust and Nonlinear Control 31(2) (2021) 380–403.
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2020 | Book Chapter | LibreCat-ID: 17411
Symmetry in Optimal Control: A Multiobjective Model Predictive Control Approach
K. Flaßkamp, S. Ober-Blöbaum, S. Peitz, in: O. Junge, O. Schütze, G. Froyland, S. Ober-Blöbaum, K. Padberg-Gehle (Eds.), Advances in Dynamics, Optimization and Computation, Springer, Cham, 2020.
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2020 | Journal Article | LibreCat-ID: 10596
Pareto Explorer: a global/local exploration tool for many-objective optimization problems
O. Schütze, O. Cuate, A. Martín, S. Peitz, M. Dellnitz, Engineering Optimization 52 (2020) 832–855.
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2020 | Journal Article | LibreCat-ID: 16288
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, C. Schütte, Physica D: Nonlinear Phenomena 406 (2020).
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2020 | Book Chapter | LibreCat-ID: 16289
Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator
S. Peitz, S. Klus, in: Lecture Notes in Control and Information Sciences, Springer, Cham, 2020, pp. 257–282.
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2020 | Journal Article | LibreCat-ID: 16290 | OA
Deep model predictive flow control with limited sensor data and online learning
K. Bieker, S. Peitz, S.L. Brunton, J.N. Kutz, M. Dellnitz, Theoretical and Computational Fluid Dynamics 34 (2020) 577–591.
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2020 | Journal Article | LibreCat-ID: 16309
Data-Driven Model Predictive Control using Interpolated Koopman Generators
S. Peitz, S.E. Otto, C.W. Rowley, SIAM Journal on Applied Dynamical Systems 19 (2020) 2162–2193.
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2020 | Journal Article | LibreCat-ID: 16297
Explicit Multi-objective Model Predictive Control for Nonlinear Systems Under Uncertainty
C.I. Hernández Castellanos, S. Ober-Blöbaum, S. Peitz, International Journal of Robust and Nonlinear Control 30(17) (2020) 7593–7618.
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2019 | Journal Article | LibreCat-ID: 10593
Koopman operator-based model reduction for switched-system control of PDEs
S. Peitz, S. Klus, Automatica 106 (2019) 184–191.
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2019 | Journal Article | LibreCat-ID: 10595
On the hierarchical structure of Pareto critical sets
B. Gebken, S. Peitz, M. Dellnitz, Journal of Global Optimization 73 (2019) 891–913.
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2019 | Conference Paper | LibreCat-ID: 10597
Finite-Control-Set Model Predictive Control for a Permanent Magnet Synchronous Motor Application with Online Least Squares System Identification
S. Hanke, S. Peitz, O. Wallscheid, J. Böcker, M. Dellnitz, 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
Finite-control-set model predictive control for a permanent magnet synchronous motor application with online least squares system identification
S. Hanke, S. Peitz, O. Wallscheid, J. Böcker, M. Dellnitz, 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 | OA
Koopman Operator-Based Finite-Control-Set Model Predictive Control for Electrical Drives
S. Hanke, S. Peitz, O. Wallscheid, S. Klus, J. Böcker, M. Dellnitz, ArXiv:1804.00854 (2018).
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2018 | Book Chapter | LibreCat-ID: 22796
Eingesetzte wissenschaftliche Methoden
F. Kummert, A. Albers, C. Bremer, S. Büttner, M. Dellnitz, R. Dumitrescu, M. Gräler, V. Just, H. Mucha, S. Peitz, C. Röcker, A. Trächtler, C. Tschirner, S. Wang, J. Wittrowski, in: A. Trächtler (Ed.), Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts, Springer, Paderborn, 2018.
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2018 | Conference Paper | LibreCat-ID: 8750
A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems
B. Gebken, S. Peitz, M. Dellnitz, in: Numerical and Evolutionary Optimization – NEO 2017, Cham, 2018.
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2018 | Journal Article | LibreCat-ID: 8751 | OA
A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models, Feedback Control and Objective Reduction
S. Peitz, M. Dellnitz, Mathematical and Computational Applications 23 (2018).
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2018 | Book Chapter | LibreCat-ID: 8754
Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition
D. Beermann, M. Dellnitz, S. Peitz, S. Volkwein, in: Reduced-Order Modeling (ROM) for Simulation and Optimization, Cham, 2018, pp. 47–72.
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