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Data-driven model predictive control: closed-loop guarantees and experimental results

Data-driven model predictive control: closed-loop guarantees and experimental results AbstractWe provide a comprehensive review and practical implementation of a recently developed model predictive control (MPC) framework for controlling unknown systems using only measured data and no explicit model knowledge. Our approach relies on an implicit system parametrization from behavioral systems theory based on one measured input-output trajectory. The presented MPC schemes guarantee closed-loop stability for unknown linear time-invariant (LTI) systems, even if the data are affected by noise. Further, we extend this MPC framework to control unknown nonlinear systems by continuously updating the data-driven system representation using new measurements. The simple and intuitive applicability of our approach is demonstrated with a nonlinear four-tank system in simulation and in an experiment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png at - Automatisierungstechnik de Gruyter

Data-driven model predictive control: closed-loop guarantees and experimental results

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Publisher
de Gruyter
Copyright
© 2021 Berberich et al., published by De Gruyter
ISSN
2196-677X
eISSN
2196-677X
DOI
10.1515/auto-2021-0024
Publisher site
See Article on Publisher Site

Abstract

AbstractWe provide a comprehensive review and practical implementation of a recently developed model predictive control (MPC) framework for controlling unknown systems using only measured data and no explicit model knowledge. Our approach relies on an implicit system parametrization from behavioral systems theory based on one measured input-output trajectory. The presented MPC schemes guarantee closed-loop stability for unknown linear time-invariant (LTI) systems, even if the data are affected by noise. Further, we extend this MPC framework to control unknown nonlinear systems by continuously updating the data-driven system representation using new measurements. The simple and intuitive applicability of our approach is demonstrated with a nonlinear four-tank system in simulation and in an experiment.

Journal

at - Automatisierungstechnikde Gruyter

Published: Jul 27, 2021

Keywords: data-driven control; model predictive control; nonlinear systems; datenbasierte Regelung; prädiktive Regelung; nichtlineare Systeme

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