Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control

S. Alireza Davari, Vahab Nekoukar, Cristian Garcia, Jose Rodriguez

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

4 Citas (Scopus)

Resumen

Model predictive control brings many advantages and it simplifies the control scheme in power electronics. However, tuning the weighting factor is one of the important open discussions on this topic. There are online and offline methods that have been introduced to select the weighting factor. The online methods are preferred because they are more feasible. In this article, an online weighting factor optimization method based on the simulated annealing algorithm is proposed. The energy of the ripple is used as a convergence criterion. The presented method can be converged in a few steps and it does not impose cumbersome computations. Therefore, the optimal voltage will be identical for a range of the weighting factor. Furthermore, the used search algorithm is parameter independent. The proposed method is implemented for an induction motor but it is also applicable for other applications. The proposed method is validated by the experimental tests.

Idioma originalInglés
Número de artículo9040651
Páginas (desde-hasta)31-40
Número de páginas10
PublicaciónIEEE Transactions on Industrial Informatics
Volumen17
N.º1
DOI
EstadoPublicada - ene 2021

Áreas temáticas de ASJC Scopus

  • Ingeniería de control y sistemas
  • Sistemas de información
  • Informática aplicada
  • Ingeniería eléctrica y electrónica

Huella

Profundice en los temas de investigación de 'Online Weighting Factor Optimization by Simplified Simulated Annealing for Finite Set Predictive Control'. En conjunto forman una huella única.

Citar esto