Speaker
Manuel Schaller
Description
Extended Dynamic Mode Decomposition is a popular data-driven method to approximate the flow of a dynamical control system through the lens of observable functions. In this talk, we discuss how this framework and corresponding finite-data error bounds may be used in data-driven Model Predictive Control to establish (practical) asymptotic stability. The key ingredient are proportional error bounds vanishing at the origin, which may be utilized to show that important system-theoretic properties, such as cost controllability, carry over to the data-driven model, if a sufficient amount of samples is chosen.
Author
Manuel Schaller
Co-authors
Prof.
Karl Worthmann
(Technische Universität Ilmenau)
Prof.
Lars Grüne
(University of Bayreuth)
Lea Bold
(Technische Universität Ilmenau)
