A MRAS-based adaptive pseudoreduced-order flux observer for sensorless induction motor drives

The performance of vector-controlled sensorless induction motor drives is generally poor at very low speeds, especially at zero speed due to offset and drift components in the acquired feedback signals, and the increased sensitivity of dynamic performance to model parameter mismatch resulting especi...

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Bibliographic Details
Published in:IEEE transactions on power electronics 2005-07, Vol.20 (4), p.930-938
Main Authors: Kojabadi, H.M., Liuchen Chang, Doraiswami, R.
Format: Article
Language:English
Subjects:
Adaptive observers
Applied sciences
Comparative analysis
Dynamics
Electrical engineering. Electrical power engineering
Electrical machines
Electronics
Estimating techniques
estimation
Exact sciences and technology
Feedback
Flux
Frequency estimation
Induction motor drives
Induction motors
Low speed
Lyapunov method
Mathematical models
model reference adaptive control
Motors
Observers
Performance evaluation
Power electronics, power supplies
Power supply
Regulation and control
Sensorless control
sensorless control scheme
Shafts
Stators
Temperature sensors
Velocity control
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Summary:The performance of vector-controlled sensorless induction motor drives is generally poor at very low speeds, especially at zero speed due to offset and drift components in the acquired feedback signals, and the increased sensitivity of dynamic performance to model parameter mismatch resulting especially from stator resistance variations. The speed estimation is adversely affected by stator resistance variations due to temperature and frequency changes. This is particularly significant at very low speeds where the calculated flux deviates from its set values. Therefore, it is necessary to compensate for the parameter variation in sensorless induction motor drives, particularly at very low speeds. This paper presents a novel method of estimating both the shaft speed and stator resistance of an induction motor. In this novel scheme, an adaptive pseudoreduced-order flux observer (APFO) is developed. In comparison to the adaptive full-order flux observer (AFFO), the proposed method consumes less computational time, and provides a better stator resistance estimation dynamic performance. Both simulation and experimental results confirm the superiority of the proposed APFO scheme for a wide range of resistance variations from 0 to 100%.
ISSN:0885-8993
1941-0107
DOI:10.1109/TPEL.2005.850969