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Titel:

Enhanced Sensorless Model Predictive Control of Induction Motor Based on Extended Kalman Filter

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Ahmed Ibrahim Soliman ; Ahmed Farhan ; Mohamed Abdelrahem ; Ralph Kennel
Abstract:
This paper presents an enhanced method for a self-sensing (Sensorless) Model Predictive Control (MPC) of Induction Motor (IM) supplied form two-level using state-space model. For the self-sensing process, the controller needs a proper position and speed observer. In this paper, the position and speed of the rotor are estimated based on Extended Kalman Filter (EKF). The proposed EKF is executed to achieve a small error in the estimation parameters of IM in transient and steady-state operation. Mo...     »
Kongress- / Buchtitel:
Proceeding of the 2019 IEEE Conference on Power Electronics and Renewable Energy (CPERE)
Datum der Konferenz:
23-25 Oct. 2019
Jahr:
2020
Quartal:
1. Quartal
Jahr / Monat:
2020-02
Monat:
Feb
Print-ISBN:
978-1-7281-0911-4
E-ISBN:
978-1-7281-0910-7
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/CPERE45374.2019.8980031
Semester:
WS 19-20
TUM Einrichtung:
Lehrstuhl für Elektrische Antriebssysteme und Leistungselektronik
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