@inproceedings{30125, abstract = {{We present an approach for guaranteed constraint satisfaction by means of data-based optimal control, where the model is unknown and has to be obtained from measurement data. To this end, we utilize the Koopman framework and an eDMD-based bilinear surrogate modeling approach for control systems to show an error bound on predicted observables, i.e., functions of the state. This result is then applied to the constraints of the optimal control problem to show that satisfaction of tightened constraints in the purely data-based surrogate model implies constraint satisfaction for the original system.}}, author = {{Schaller, Manuel and Worthmann, Karl and Philipp, Friedrich and Peitz, Sebastian and Nüske, Feliks}}, booktitle = {{IFAC-PapersOnLine}}, number = {{1}}, pages = {{169--174}}, title = {{{Towards reliable data-based optimal and predictive control using extended DMD}}}, doi = {{10.1016/j.ifacol.2023.02.029}}, volume = {{56}}, year = {{2023}}, }