Multiobjective Fuzzy-Decision-Making Predictive Torque Control for an Induction Motor Drive

Christian A. Rojas, Jose R. Rodriguez, Samir Kouro, Felipe Villarroel

Resultado de la investigación: Article

36 Citas (Scopus)

Resumen

In the recent years, the use of model predictive control in electrical drives has been widely reported both theoretically and experimentally. Predictive torque control has been developed to control induction motor drives, allowing high performance and fast dynamics. However, the optimization used in predictive torque control is based on a single cost function minimization, where control objectives are merged by using weighting factors. The selection of these scalar factors is achieved through offline and online search methods and they are heavily dependent on the system parameters. To avoid this drawback, a multiobjective fuzzy predictive torque control is presented. The proposed strategy replaces the minimization of a scalar cost function with a multiobjective optimization using fuzzy decision making. Experimental implementation is presented to validate the performance of the proposed control scheme.

Idioma originalEnglish
Número de artículo7600354
Páginas (desde-hasta)6245-6260
Número de páginas16
PublicaciónIEEE Transactions on Power Electronics
Volumen32
N.º8
DOI
EstadoPublished - 1 ago 2017

Huella dactilar

Torque control
Induction motors
Decision making
Cost functions
Model predictive control
Multiobjective optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Citar esto

Rojas, Christian A. ; Rodriguez, Jose R. ; Kouro, Samir ; Villarroel, Felipe. / Multiobjective Fuzzy-Decision-Making Predictive Torque Control for an Induction Motor Drive. En: IEEE Transactions on Power Electronics. 2017 ; Vol. 32, N.º 8. pp. 6245-6260.
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Multiobjective Fuzzy-Decision-Making Predictive Torque Control for an Induction Motor Drive. / Rojas, Christian A.; Rodriguez, Jose R.; Kouro, Samir; Villarroel, Felipe.

En: IEEE Transactions on Power Electronics, Vol. 32, N.º 8, 7600354, 01.08.2017, p. 6245-6260.

Resultado de la investigación: Article

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