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Classic, fuzzy and pbkp_redictive dtc strategies for the PMSM using the bacterial foraging algorithmas an online parameter estimator

Abstract:

This work presents a comparison between four control techniques applied to drive a PMSM: Classic DTC, Modified DTC with a Fuzzy Inference System, Pbkp_redictive DTC and Pbkp_redictive DTC with Fuzzy Inference System. Parameters estimation for the pbkp_redictive strategies is performed using a population-based search algorithm (Bacterial Foraging), which is able to calculate on line the PMSM parameters. The electric torque and stator flux linkages experimental results show that the pbkp_redictive strategies that use the machine parameters estimated by the Bacterial Foraging Algorithm present a significant improvement when compared with non pbkp_redictive techniques.

Año de publicación:

2012

Keywords:

  • Bacterial foraging
  • PMSM
  • DTC
  • Parameter estimation
  • Fuzzy Inference System
  • Pbkp_redictive control

Fuente:

scopusscopus
googlegoogle

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Algoritmo
  • Aprendizaje automático

Áreas temáticas:

    Contribuidores:

    Guzman V.M.Guzman V.M.
    Gimenez M.I.Gimenez M.I.
    J. M. AllerJ. M. Aller
    José Manuel Aller CastroJosé Manuel Aller Castro
    Jose Alex RestrepoJose Alex Restrepo
    Noriega G.Noriega G.
    Bueno M A.Bueno M A.