A robust adaptive model predictive control framework for nonlinear uncertain systems

In this paper, we present a tube-based framework for robust adaptive model predictive control (RAMPC) for nonlinear systems subject to parametric uncertainty and additive disturbances. Set-membership estimation is used to provide accurate bounds on the parametric uncertainty, which are employed for...

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Vydané v:	arXiv.org
Hlavní autori:	Köhler, Johannes, Kötting, Peter, Soloperto, Raffaele, Allgöwer, Frank, Müller, Matthias A
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 20.10.2020
Predmet:	Adaptive control Algorithms Constraint modelling Disturbances Feasibility Liapunov functions Nonlinear control Nonlinear systems Parameter estimation Predictive control Robust control Robustness (mathematics) Uncertainty
ISSN:	2331-8422
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