Luenberger Prediction Model-Based Robust Predictive Current Control of Induction Machine Drives

Liming Yan, Fengxiang Wang, Jose Rodriguez

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

Resumen

For model predictive current control of induction machine drives, the mismatched parameters of induction motors inevitably lead to model prediction errors, reduce dynamic and steady-state performances, and even cause the system instability. In view of this problem, this paper proposed a Luenberger prediction model-based robust predictive current control (LPM-PCC), where stator current is predicted by a closed-loop prediction mode. In addition, the stator current prediction errors are analyzed for the tradition predictive current control (T-PCC) and the proposed LPM-PCC. The experimental results verify the effectiveness of the proposed LPM-PCC.

Idioma originalInglés
Título de la publicación alojada2020 IEEE 9th International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas1006-1010
Número de páginas5
ISBN (versión digital)9781728153018
DOI
EstadoPublicada - 29 nov 2020
Evento9th IEEE International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia - Nanjing, China
Duración: 29 nov 20202 dic 2020

Serie de la publicación

Nombre2020 IEEE 9th International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia

Conferencia

Conferencia9th IEEE International Power Electronics and Motion Control Conference, IPEMC 2020 ECCE Asia
País/TerritorioChina
CiudadNanjing
Período29/11/202/12/20

Áreas temáticas de ASJC Scopus

  • Ingeniería energética y tecnologías de la energía
  • Ingeniería eléctrica y electrónica
  • Control y optimización

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