Sebastian Peitz
Sebastian Peitz
Assistant Professor for "Data Science for Engineering", Paderborn University
Zweryfikowany adres z upb.de - Strona główna
Cytowane przez
Cytowane przez
Koopman operator-based model reduction for switched-system control of PDEs
S Peitz, S Klus
Automatica 106, 184-191, 2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
S Klus, F Nüske, S Peitz, JH Niemann, C Clementi, C Schütte
Physica D: Nonlinear Phenomena 406, 132416, 2020
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 (2), 2018
Deep model predictive flow control with limited sensor data and online learning
K Bieker, S Peitz, SL Brunton, JN Kutz, M Dellnitz
Theoretical and Computational Fluid Dynamics 34, 577–591, 2020
Tensor-based dynamic mode decomposition
S Klus, P Gelß, S Peitz, C Schütte
Nonlinearity 31 (7), 3359, 2018
Gradient-based multiobjective optimization with uncertainties
S Peitz, M Dellnitz
NEO 2016, 159-182, 2018
Data-Driven Model Predictive Control using Interpolated Koopman Generators
S Peitz, SE Otto, CW Rowley
SIAM Journal on Applied Dynamical Systems 19 (3), 2162-2193, 2020
Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling
S Peitz, S Ober-Blöbaum, M Dellnitz
Acta Applicandae Mathematicae 161 (1), 171-199, 2019
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 (5), 832-855, 2020
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 preprint arXiv:1804.00854, 2018
A multiobjective MPC approach for autonomously driven electric vehicles
S Peitz, K Schäfer, S Ober-Blöbaum, J Eckstein, U Köhler, M Dellnitz
IFAC-PapersOnLine 50 (1), 8674-8679, 2017
On the hierarchical structure of Pareto critical sets
B Gebken, S Peitz, M Dellnitz
Journal of Global Optimization 73 (4), 891-913, 2019
Exploiting Structure in Multiobjective Optimization and Optimal Control
S Peitz
Paderborn University, 2017
Set-Oriented Multiobjective Optimal Control of PDEs using Proper Orthogonal Decomposition
D Beermann, M Dellnitz, S Peitz, S Volkwein
Reduced-Order Modeling for Simulation and Optimization: Powerful Algorithms …, 2017
Development of an intelligent cruise control using optimal control methods
M Dellnitz, J Eckstein, K Flaßkamp, P Friedel, C Horenkamp, U Köhler, ...
Procedia Technology 15, 285-294, 2014
A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems
B Gebken, S Peitz, M Dellnitz
Numerical and Evolutionary Optimization – NEO 2017, 29-61, 2017
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
IEEE International Symposium on Predictive Control of Electrical Drives and …, 2019
A comparison of two predictive approaches to control the longitudinal dynamics of electric vehicles
J Eckstein, S Peitz, K Schäfer, P Friedel, U Köhler, M Hessel-von Molo, ...
Procedia Technology 26, 465-472, 2016
Controlling nonlinear PDEs using low-dimensional bilinear approximations obtained from data
S Peitz
arXiv preprint arXiv:1801.06419, 2018
An efficient descent method for locally Lipschitz multiobjective optimization problems
B Gebken, S Peitz
Journal of Optimization Theory and Applications 188, 696-723, 2021
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