@article{10593,
abstract = {We present a new framework for optimal and feedback control of PDEs using Koopman operator-based reduced order models (K-ROMs). The Koopman operator is a linear but infinite-dimensional operator which describes the dynamics of observables. A numerical approximation of the Koopman operator therefore yields a linear system for the observation of an autonomous dynamical system. In our approach, by introducing a finite number of constant controls, the dynamic control system is transformed into a set of autonomous systems and the corresponding optimal control problem into a switching time optimization problem. This allows us to replace each of these systems by a K-ROM which can be solved orders of magnitude faster. By this approach, a nonlinear infinite-dimensional control problem is transformed into a low-dimensional linear problem. Using a recent convergence result for the numerical approximation via Extended Dynamic Mode Decomposition (EDMD), we show that the value of the K-ROM based objective function converges in measure to the value of the full objective function. To illustrate the results, we consider the 1D Burgers equation and the 2D Navierâ€“Stokes equations. The numerical experiments show remarkable performance concerning both solution times and accuracy.},
author = {Peitz, Sebastian and Klus, Stefan},
issn = {0005-1098},
journal = {Automatica},
pages = {184--191},
title = {{Koopman operator-based model reduction for switched-system control of PDEs}},
doi = {10.1016/j.automatica.2019.05.016},
volume = {106},
year = {2019},
}