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Comparison of two novel MRAS based strategies for identifying parameters in permanent magnet synchronous motors

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journal contribution
posted on 2017-05-18, 13:50 authored by Kan Liu, Qiao Zhang, Zi-Qiang Zhu, Jing Zhang, An-Wen Shen, Paul Stewart
Two model reference adaptive system (MRAS) estimators are developed for identifying the parameters of permanent magnet synchronous motors (PMSM) based on the Lyapunov stability theorem and the Popov stability criterion, respectively. The proposed estimators only need online measurement of currents, voltages, and rotor speed to effectively estimate stator resistance, inductance, and rotor flux-linkage simultaneously. The performance of the estimators is compared and verified through simulations and experiments, which show that the two estimators are simple, have good robustness against parameter variation, and are accurate in parameter tracking. However, the estimator based on the Popov stability criterion, which can overcome parameter variation in a practical system, is superior in terms of response speed and convergence speed since there are both proportional and integral units in the estimator, in contrast to only one integral unit in the estimator based on the Lyapunov stability theorem. In addition, the estimator based on the Popov stability criterion does not need the expertise that is required in designing a Lyapunov function. © 2010 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.

Funding

This work was supported by China Scholarship Council, National Natural Science Foundation of China (No. 60634020) and Scientific Research Foundation of Education Ministry for the Doctors (No. 20060532026).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

International Journal of Automation and Computing

Volume

7

Issue

4

Pages

516 - 524

Citation

LIU, K., 2010. Comparison of two novel MRAS based strategies for identifying parameters in permanent magnet synchronous motors. International Journal of Automation and Computing, 7(4), pp. 516-524.

Publisher

© Springer

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2010

Notes

The final publication is available at Springer via http://dx.doi.org/10.1007/s11633-010-0535-3

ISSN

1476-8186

eISSN

1751-8520

Language

  • en