C. I. Hernández Castellanos, S. Ober-Blöbaum, and S. Peitz, “Explicit Multi-objective Model Predictive Control for Nonlinear Systems  Under Uncertainty,”10.1002/rnc.5197__International Journal of Robust and Nonlinear Control, vol. 30(17), pp. 7593–7618, 2020, doi:10.1002/rnc.5197 .
LibreCat: /record/16297
DOI: 10.1002/rnc.5197

S. Peitz and S. Klus, “Koopman operator-based model reduction for switched-system control of PDEs,” Automatica, vol. 106, pp. 184–191, 2019.
LibreCat: /record/10593
DOI: 10.1016/j.automatica.2019.05.016

B. Gebken, S. Peitz, and M. Dellnitz, “On the hierarchical structure of Pareto critical sets,” Journal of Global Optimization, vol. 73, no. 4, pp. 891–913, 2019.
LibreCat: /record/10595
DOI: 10.1007/s10898-019-00737-6

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.
LibreCat: /record/10597
DOI: 10.1109/precede.2019.8753313

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.
LibreCat: /record/29636

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.
LibreCat: /record/21634

F. Kummert et al., “Eingesetzte wissenschaftliche Methoden,” in Ressourceneffiziente Selbstoptimierende Wäscherei – Ergebnisse des ReSerW-Projekts, A. Trächtler, Ed. Paderborn: Springer, 2018.
LibreCat: /record/22796

B. Gebken, S. Peitz, and M. Dellnitz, “A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems,” in Numerical and Evolutionary Optimization – NEO 2017, 2018.
LibreCat: /record/8750
DOI: 10.1007/978-3-319-96104-0_2

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.
LibreCat: /record/8751
DOI: 10.3390/mca23020030

D. Beermann, M. Dellnitz, S. Peitz, and S. Volkwein, “Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition,” in Reduced-Order Modeling (ROM) for Simulation and Optimization, Cham, 2018, pp. 47–72.
LibreCat: /record/8754
DOI: 10.1007/978-3-319-75319-5_3

S. Klus, P. Gelß, S. Peitz, and C. Schütte, “Tensor-based dynamic mode decomposition,” Nonlinearity, vol. 31, no. 7, pp. 3359–3380, 2018.
LibreCat: /record/8755
DOI: 10.1088/1361-6544/aabc8f

D. Beermann, M. Dellnitz, S. Peitz, and S. Volkwein, “POD-based multiobjective optimal control of PDEs with non-smooth objectives,” in PAMM, 2018, pp. 51–54.
LibreCat: /record/8757
DOI: 10.1002/pamm.201710015

S. Peitz, “Controlling nonlinear PDEs using low-dimensional bilinear approximations  obtained from data,” arXiv:1801.06419. 2018.
LibreCat: /record/16292

S. Klus, S. Peitz, and I. Schuster, “Analyzing high-dimensional time-series data using kernel transfer  operator eigenfunctions,” arXiv:1805.10118. 2018.
LibreCat: /record/16293

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 preprint arXiv:1804.00854, 2018.
LibreCat: /record/29624

S. Peitz, S. Ober-Blöbaum, and M. Dellnitz, “Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling,”10.1007/s10440-018-0209-7__Acta Applicandae Mathematicae, vol. 161, no. 1, pp. 171–199, 2018, doi:10.1007/s10440-018-0209-7 .
LibreCat: /record/8753
DOI: 10.1007/s10440-018-0209-7

M. Dellnitz et al., “Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control,” in Progress in Industrial Mathematics at ECMI 2014 , 2017, pp. 633–641.
LibreCat: /record/5914
DOI: 10.1007/978-3-319-23413-7_87

S. Peitz and M. Dellnitz, “Gradient-Based Multiobjective Optimization with Uncertainties,” in NEO 2016, 2017, pp. 159–182.
LibreCat: /record/8752
DOI: 10.1007/978-3-319-64063-1_7

S. Peitz,   Exploiting structure in multiobjective optimization and optimal control. 2017.
LibreCat: /record/10594
DOI: 10.17619/UNIPB/1-176

S. Peitz, K. Schäfer, S. Ober-Blöbaum, J. Eckstein, U. Köhler, and M. Dellnitz, “A multiobjective MPC approach for autonomously driven electric vehicles,”10.1016/j.ifacol.2017.08.1526__Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC), vol. 50, no. 1, pp. 8674–8679, 2017, doi:10.1016/j.ifacol.2017.08.1526 .
LibreCat: /record/8756
DOI: 10.1016/j.ifacol.2017.08.1526