Parameter estimation of permanent magnet synchronous motor
https://doi.org/10.17586/2226-1494-2023-23-6-1242-1246
Abstract
The problem of estimating the parameters of non-salient synchronous motor with surface-mounted permanent magnets is considered. A parameterization of a nonlinear motor model is proposed, which allows obtaining a linear regressor equation using measured (estimated) values of current and voltage in the stator windings and the angular rotor position. Using the method of dynamic regressor extension and mixing, an algorithm for estimating the desired parameters in finite time is designed.
Keywords
About the Authors
A. A. PyrkinRussian Federation
Anton A. Pyrkin — D.Sc., Full Professor
Saint Petersburg, 197101
sc 26656070700
A. A. Vedyakov
Russian Federation
Alexey A. Vedyakov — PhD, Associate Professor, Associate Professor
Saint Petersburg, 197101
sc 49664023200
A. K. Golubev
Russian Federation
Anton K. Golubev — PhD Student, Assistant
Saint Petersburg, 197101
References
1. Sakunthala S., Kiranmayi R., Mandadi P.N. A review on speed control of permanent magnet synchronous motor drive using different control techniques. Proc. of the 2018 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), 2018, pp. 97– 102. https://doi.org/10.1109/icpects.2018.8521574
2. Bobtsov A.A., Pyrkin A.A., Ortega R., Vukosavic S.N., Stankovic A.M., Panteley E.V. A robust globally convergent position observer for the permanent magnet synchronous motor. Automatica, 2015, vol. 61, pp. 47–54. https://doi.org/10.1016/j.automatica.2015.07.032
3. Ortega R., Monshizadeh N., Monshizadeh P., Bazylev D., Pyrkin A. Permanent magnet synchronous motors are globally asymptotically stabilizable with PI current control. Automatica, 2018, vol. 98, pp. 296–301. https://doi.org/10.1016/j.automatica.2018.09.031
4. Nam K.H. AC Motor Control and Electric Vehicle Applications. CRC Press, 2010, 435 p.
5. Aranovskiy S., Bobtsov A., Ortega R., Pyrkin A. Performance enhancement of parameter estimators via dynamic regressor extension and mixing. IEEE Transactions on Automatic Control, 2017, vol. 62, no. 7, pp. 3546–3550. https://doi.org/10.1109/tac.2016.2614889
6. Ortega R., Aranovskiy S., Pyrkin A.A., Astolfi A., Bobtsov A.A. New results on parameter estimation via dynamic regressor extension and mixing: Continuous and discrete-time cases. IEEE Transactions on Automatic Control, 2021, vol. 66, no. 5, pp. 2265–2272. https://doi.org/10.1109/tac.2020.3003651
7. Pyrkin A., Bobtsov A., Ortega R., Vedyakov A., Aranovskiy S. Adaptive state observers using dynamic regressor extension and mixing. Systems & Control Letters, 2019, vol. 133, pp. 104519. https://doi.org/10.1016/j.sysconle.2019.104519
8. Pyrkin A., Bobtsov A., Ortega R., Vedyakov A., Cherginets D., Ovcharov A., Bazylev D., Petranevsky I. Robust nonlinear observer design for permanent magnet synchronous motors. IET Control Theory & Applications, 2021, vol. 15, no. 4, pp. 604–616. https://doi.org/10.1049/cth2.12065
9. Jang J.H., Ha J.I., Ohto M., Ide K., Sul S.K. Analysis of permanentmagnet machine for sensorless control based on high-frequency signal injection. IEEE Transactions on Industry Applications, 2004, vol. 40, no. 6, pp. 1595–1604. https://doi.org/10.1109/tia.2004.836222
10. Pyrkin A.A., Vedyakov A.A., Ortega R., Bobtsov A.A. A robust adaptive flux observer for a class of electromechanical systems. International Journal of Control, 2020, vol. 93, no. 7, pp. 1619–1629. https://doi.org/10.1080/00207179.2018.1521995
Review
For citations:
Pyrkin A.A., Vedyakov A.A., Golubev A.K. Parameter estimation of permanent magnet synchronous motor. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2023;23(6):1242-1246. (In Russ.) https://doi.org/10.17586/2226-1494-2023-23-6-1242-1246