Eliminating Current Sensors in Simplified Predictive Direct Voltage Control of RSM

Arash Fereidooni, S. Alireza Davari, Cristian Garcia, Jose Rodriguez

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

Resumen

Reluctance synchronous motor (RSM) has attracted the attentions because of its high efficiency. The predictive control, as an advanced control method, has also been used to control this motor. The simplified FCS-MPC (finite control set model predictive control) method has become a successful version of the predictive control because of its simplicity, reduced computation, and elimination of the weighting factor. In this method, to predict the current, it is necessary to have two current sensors to measure the currents. Therefore, the possible failure of the current sensors will stop the process in the control loop. In this paper, the elimination of all current sensors via an observer is proposed for the simplified FCS-MPC method. This issue will increase the reliability of the control method. Also, removing the current sensors reduces the cost of the hardware. The performance of this observer has been evaluated by simulation.

Idioma originalInglés
Título de la publicación alojada2020 11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728158495
DOI
EstadoPublicada - feb 2020
Evento11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020 - Tehran, República Islámica de Irán
Duración: 4 feb 20206 feb 2020

Serie de la publicación

Nombre2020 11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020

Conferencia

Conferencia11th Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2020
País/TerritorioRepública Islámica de Irán
CiudadTehran
Período4/02/206/02/20

Áreas temáticas de ASJC Scopus

  • Ingeniería energética y tecnologías de la energía
  • Energías renovables, sostenibilidad y medio ambiente
  • Ingeniería automovilística
  • Ingeniería eléctrica y electrónica
  • Ingeniería mecánica
  • Control y optimización

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