Publications

@conference{Ivanov2022138,

title = {On Instrumental Variable-Based Method for Identification of Permanent Magnet Synchronous Machine by Noisy Data},

author = {D. V. Ivanov and I. L. Sandler and Z. Yakoub and V. V. Antonova and M. A. Terekhin and L. A. Bezyazykova},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146109772\&doi=10.1109%2fSUMMA57301.2022.9973900\&partnerID=40\&md5=2481f25c8f6f96b277912274f9c4c95d},

doi = {10.1109/SUMMA57301.2022.9973900},

isbn = {9781665456593},

year  = {2022},

date = {2022-01-01},

journal = {Proceedings - 2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2022},

pages = {138-142},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {The identification of parameters of the permanent magnet synchronous machine (PMSM) is considered. The paper uses a discrete model of the permanent magnet synchronous machine. The proposed algorithm makes it possible to consider the errors in measurements of current, voltage, and electrical angular speed. Extended instrument variables are used to identify parameters. To solve the overdetermined system, total least squares are used. This makes it possible to improve the accuracy of estimates of extended instrumental variables on a finite sample. The simulation results confirmed the high accuracy of the resulting estimates. © 2022 IEEE.},

note = {cited By 2},

keywords = {Augmented system of equation; Augmented systems; Error-in-variable; Extended instrumental variable; Instrumental variables; Noisy data; Permanent magnet synchronoi machine; Permanent magnets synchronous machines; Systems of equations; Total least squares, Least squares approximations; Sampling; Synchronous machinery, Permanent magnets},

pubstate = {published},

tppubtype = {conference}

}