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Nonlinear Data-Enabled Prediction and Control

Published 8 Jan 2021 in math.OC, cs.SY, and eess.SY | (2101.03187v2)

Abstract: 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.

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