Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
Revista Facultad de Ingeniería Universidad de Antioquia
versión impresa ISSN 0120-6230
Resumen
NORIEGA, Gabriel et al. Classic, fuzzy and predictive dtc strategies for the PMSM using the bacterial foraging algorithmas an online parameter estimator. Rev.fac.ing.univ. Antioquia [online]. 2012, n.64, pp.182-194. ISSN 0120-6230.
This work presents a comparison between four control techniques applied to drive a PMSM: Classic DTC, Modified DTC with a Fuzzy Inference System, Predictive DTC and Predictive DTC with Fuzzy Inference System. Parameters estimation for the predictive 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 predictive strategies that use the machine parameters estimated by the Bacterial Foraging Algorithm present a significant improvement when compared with non predictive techniques.
Palabras clave : PMSM; DTC; bacterial foraging; fuzzy inference system; parameter estimation; predictive control.