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Speed sensorless direct torque control of induction motors using an adaptive flux observer

Maes, J., Melkebeek, J.·2003·Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370)

Abstract

The authors present a new sensorless induction motor drive. The drive uses an adaptive flux observer for speed estimation and the discrete-time direct torque control technique for torque and stator flux control. The adaptive flux observer uses a mechanical model to improve the behavior during speed transients. The estimated stator flux of the adaptive observer is used in the discrete-time direct torque control method to provide fast torque response combined with torque ripple free operation over the whole speed range. The sensorless drive system is capable of working from very low speed to high speed and exhibits good dynamic and steady state performance. The authors demonstrate the steady state and dynamic performance of the proposed sensorless drive using simulation and experimental results.

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Metadata

Authors
Maes, J., & Melkebeek, J.
Venue
Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370)
Publisher
IEEE
Published
2003-01-20
Volume
4
Pages
2305-2312
OpenAlex
W2125214425
Cited by
267
References
0
FWCI
22.96
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Speed sensorless direct torque control of induction motors using an adaptive flux observer. https://app.cochat.ai/papers/10.1109/ias.1999.799165
The paper
Maes, J., & Melkebeek, J. (2003). Speed sensorless direct torque control of induction motors using an adaptive flux observer. Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370). https://doi.org/10.1109/ias.1999.799165

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.