Classic, fuzzy and predictive 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, 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.
Año de publicación:
2012
Keywords:
- Bacterial foraging
- PMSM
- DTC
- Parameter estimation
- Fuzzy Inference System
- Pbkp_redictive control
Fuente:


Tipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
- Algoritmo
- Aprendizaje automático
Áreas temáticas de Dewey:

Objetivos de Desarrollo Sostenible:
- ODS 9: Industria, innovación e infraestructura
- ODS 7: Energía asequible y no contaminante
- ODS 8: Trabajo decente y crecimiento económico
