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Data-based Robust MPC with Componentwise Holder Kinky Inference

Autores

MANZANO CRESPO, JOSÉ MARÍA, Limon, D. , de la Pena, D. Munoz , Calliess, J. P. , IEEE

Publicación externa

No

Medio

Proc IEEE Conf Decis Control

Alcance

Proceedings Paper

Naturaleza

Científica

Cuartil JCR

Cuartil SJR

Fecha de publicacion

01/01/2019

ISI

000560779005145

Abstract

The authors have recently developed predictive controllers based on prediction models derived from experimental data, by means of a class of Holder interpolation called kinky inference. This paper provides a step forward by proposing a novel estimation method based on componentwise Holder interpolation. This allows to explicitly consider the contribution of each component on each output, yielding better estimations. Following the procedure used in previous works, this estimation method is used to provide a predictor for a nonlinear robust data-based predictive controller, whose performance and robustness is enhanced by the new setting. The properties of the proposed controller are demonstrated in a case study.

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