TY - GEN
T1 - A MRAS Observer Based Sensorless Control of Doubly-Fed Reluctance Wind Turbine Generators
AU - Agha Kashkooli, M. R.
AU - Jovanovic, Milutin G.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/18
Y1 - 2020/10/18
N2 - A new model reference adaptive system (MRAS) based estimation technique for vector control of a brushlesss doubly fed reluctance generator (BDFRG) without a shaft position sensor is proposed. The rotor speed is being precisely observed in a closed-loop fashion through an iterative error eradication process between the measured and estimated secondary current angles in a stationary frame. Contrary to the existing MRAS designs reported in the BDFRG literature, the reference model only utilises direct measurements of the secondary currents with-out any machine parameters. Furthermore, the current estimates coming from the adaptive model are obtained using the measured grid voltages and currents, which has provided prospects for much higher accuracy and superior overall performance. The realistic simulations and the accompanying parameter sensitivity studies have shown the great controller potential for typical operating conditions of wind turbines as the main target application.
AB - A new model reference adaptive system (MRAS) based estimation technique for vector control of a brushlesss doubly fed reluctance generator (BDFRG) without a shaft position sensor is proposed. The rotor speed is being precisely observed in a closed-loop fashion through an iterative error eradication process between the measured and estimated secondary current angles in a stationary frame. Contrary to the existing MRAS designs reported in the BDFRG literature, the reference model only utilises direct measurements of the secondary currents with-out any machine parameters. Furthermore, the current estimates coming from the adaptive model are obtained using the measured grid voltages and currents, which has provided prospects for much higher accuracy and superior overall performance. The realistic simulations and the accompanying parameter sensitivity studies have shown the great controller potential for typical operating conditions of wind turbines as the main target application.
KW - Adaptive Systems
KW - Brushless Machines
KW - Sensorless Control
KW - Velocity Control
KW - Wind Energy Conversion
UR - http://www.scopus.com/inward/record.url?scp=85097747646&partnerID=8YFLogxK
U2 - 10.1109/IECON43393.2020.9255202
DO - 10.1109/IECON43393.2020.9255202
M3 - Conference contribution
AN - SCOPUS:85097747646
T3 - IECON Proceedings (Industrial Electronics Conference)
SP - 1734
EP - 1739
BT - Proceedings - IECON 2020
PB - IEEE
T2 - 46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Y2 - 19 October 2020 through 21 October 2020
ER -