The Willems' fundamental lemma, which characterizes linear dynamics with measured trajectories, has found successful applications in controller design and signal processing, which has driven a broad research interest in its extension to nonlinear systems. In this work, we propose to apply the fundamental lemma to a reproducing kernel Hilbert space in order to extend its application to a class of nonlinear systems and we show its application in prediction and in predictive control.
@article{arxiv.2101.03187,
title = {Nonlinear Data-Enabled Prediction and Control},
author = {Yingzhao Lian and Colin N. Jones},
journal= {arXiv preprint arXiv:2101.03187},
year = {2021}
}