TY - JOUR A1 - Bittracher, Andreas A1 - Koltai, Péter A1 - Klus, Stefan A1 - Banisch, Ralf A1 - Dellnitz, Michael A1 - Schütte, Christof T1 - Transition manifolds of complex metastable systems: Theory and data-driven computation of effective dynamics JF - Jounal of Nonlinear Science N2 - We consider complex dynamical systems showing metastable behavior but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics. Y1 - 2018 U6 - https://doi.org/10.1007/s00332-017-9415-0 VL - 28 IS - 2 SP - 471 EP - 512 ER - TY - JOUR A1 - Peitz, Sebastian A1 - Gräler, Manuel A1 - Henke, Christian A1 - Hessel-von Molo, Mirko A1 - Dellnitz, Michael A1 - Trächtler, Ansgar T1 - Multiobjective Model Predictive Control of an Industrial Laundry JF - Procedia Technology N2 - In a wide range of applications, it is desirable to optimally control a system with respect to concurrent, potentially competing goals. This gives rise to a multiobjective optimal control problem where, instead of computing a single optimal solution, the set of optimal compromises, the so-called Pareto set, has to be approximated. When it is not possible to compute the entire control trajectory in advance, for instance due to uncertainties or unforeseeable events, model predictive control methods can be applied to control the system during operation in real time. In this article, we present an algorithm for the solution of multiobjective model predictive control problems. In an offline scenario, it can be used to compute the entire set of optimal compromises whereas in a real time scenario, one optimal compromise is computed according to an operator’s preference. The results are illustrated using the example of an industrial laundry. A logistics model of the laundry is developed and then utilized in the optimization routine. Results are presented for an offline as well as an online scenario Y1 - 2016 IS - 26 SP - 483 EP - 490 ER - TY - JOUR A1 - Dellnitz, Michael A1 - Hüllermeier, Eyke A1 - Lücke, Marvin A1 - Ober-Blöbaum, Sina A1 - Offen, Christian A1 - Peitz, Sebastian A1 - Pfannschmidt, Karlson T1 - Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning JF - SIAM Journal on Scientific Computing Y1 - 2023 U6 - https://doi.org/10.1137/21M1412682 VL - 45 IS - 2 SP - A579 EP - A595 ER -