On-line identification of induction motors: Experiments and results

Ashraf I. Saleem; Tarek A. Tutunji; Rateb Issa

doi:10.1109/ISMA.2008.4648798

On-line identification of induction motors: Experiments and results

Ashraf I. Saleem, Tarek A. Tutunji, Rateb Issa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Induction motors are widely used in the industry. However, due to their involved mathematical models those depend on difficult to measure parameters such as leakage inductance. Therefore, simplified model approximations are usually used instead. In this paper, a system identification method based on Auto Regressive Moving Average (ARMA) models and Hardware-in-the-Loop (HIL) concept has been employed to identify and predict the behavior of a squirrel cage induction motor. The motor transfer function is identified online using an impulse input. Then, the identified model response is compared to the real system response with different input signals. Results show that the model used follows the real system response with good accuracy.

Original language	English
Title of host publication	Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008
DOIs	https://doi.org/10.1109/ISMA.2008.4648798
Publication status	Published - 2008
Externally published	Yes
Event	5th International Symposium on Mechatronics and its Applications, ISMA 2008 - Amman, Jordan Duration: May 27 2008 → May 29 2008

Publication series

Name	Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008

Other

Other	5th International Symposium on Mechatronics and its Applications, ISMA 2008
Country/Territory	Jordan
City	Amman
Period	5/27/08 → 5/29/08

Keywords

ARMA
HIL
Identification
Induction motor

ASJC Scopus subject areas

Artificial Intelligence
Electrical and Electronic Engineering
Mechanical Engineering

Access to Document

10.1109/ISMA.2008.4648798

Cite this

Saleem, A. I., Tutunji, T. A., & Issa, R. (2008). On-line identification of induction motors: Experiments and results. In Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008 Article 4648798 (Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008). https://doi.org/10.1109/ISMA.2008.4648798

On-line identification of induction motors: Experiments and results. / Saleem, Ashraf I.; Tutunji, Tarek A.; Issa, Rateb.
Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008. 2008. 4648798 (Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Saleem, AI, Tutunji, TA & Issa, R 2008, On-line identification of induction motors: Experiments and results. in Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008., 4648798, Proceeding of the 5th International Symposium on Mechatronics and its Applications, ISMA 2008, 5th International Symposium on Mechatronics and its Applications, ISMA 2008, Amman, Jordan, 5/27/08. https://doi.org/10.1109/ISMA.2008.4648798

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title = "On-line identification of induction motors: Experiments and results",

abstract = "Induction motors are widely used in the industry. However, due to their involved mathematical models those depend on difficult to measure parameters such as leakage inductance. Therefore, simplified model approximations are usually used instead. In this paper, a system identification method based on Auto Regressive Moving Average (ARMA) models and Hardware-in-the-Loop (HIL) concept has been employed to identify and predict the behavior of a squirrel cage induction motor. The motor transfer function is identified online using an impulse input. Then, the identified model response is compared to the real system response with different input signals. Results show that the model used follows the real system response with good accuracy.",

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N2 - Induction motors are widely used in the industry. However, due to their involved mathematical models those depend on difficult to measure parameters such as leakage inductance. Therefore, simplified model approximations are usually used instead. In this paper, a system identification method based on Auto Regressive Moving Average (ARMA) models and Hardware-in-the-Loop (HIL) concept has been employed to identify and predict the behavior of a squirrel cage induction motor. The motor transfer function is identified online using an impulse input. Then, the identified model response is compared to the real system response with different input signals. Results show that the model used follows the real system response with good accuracy.

AB - Induction motors are widely used in the industry. However, due to their involved mathematical models those depend on difficult to measure parameters such as leakage inductance. Therefore, simplified model approximations are usually used instead. In this paper, a system identification method based on Auto Regressive Moving Average (ARMA) models and Hardware-in-the-Loop (HIL) concept has been employed to identify and predict the behavior of a squirrel cage induction motor. The motor transfer function is identified online using an impulse input. Then, the identified model response is compared to the real system response with different input signals. Results show that the model used follows the real system response with good accuracy.

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On-line identification of induction motors: Experiments and results

Abstract

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Keywords

ASJC Scopus subject areas

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