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pro vyhledávání: '"Mirasierra, Victor"'
Autor:
Mirasierra, Victor, Limon, Daniel
In this paper, we present the periodic modifier-adaptation formulation of the dynamic real time optimization. The proposed formulation uses gradient information to update the problem with affine modifiers so that, upon convergence, its solution match
Externí odkaz:
http://arxiv.org/abs/2309.09680
In this paper, we address the probabilistic error quantification of a general class of prediction methods. We consider a given prediction model and show how to obtain, through a sample-based approach, a probabilistic upper bound on the absolute value
Externí odkaz:
http://arxiv.org/abs/2105.14187
Autor:
Mammarella, Martina, Mirasierra, Victor, Lorenzen, Matthias, Alamo, Teodoro, Dabbene, Fabrizio
In this paper, a sample-based procedure for obtaining simple and computable approximations of chance-constrained sets is proposed. The procedure allows to control the complexity of the approximating set, by defining families of simple-approximating s
Externí odkaz:
http://arxiv.org/abs/2101.06052
Autor:
Mammarella, Martina, Mirasierra, Victor, Lorenzen, Matthias, Alamo, Teodoro, Dabbene, Fabrizio
Publikováno v:
In Automatica March 2022 137
Publikováno v:
In IFAC PapersOnLine 2020 53(2):1690-1695
Autor:
Vergara-Dietrich, José D., Mirasierra, Victor, Ferramosca, Antonio, Normey-Rico, Julio E., Limón, Daniel
Publikováno v:
In IFAC PapersOnLine 2020 53(2):6957-6962