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Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements. / Vediakova, Anastasiia O.; Vedyakov, Alexey A.

Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers. ed. / Vladimir Sukhomlin; Elena Zubareva. Springer Nature, 2020. p. 251-260 (Communications in Computer and Information Science; Vol. 1140 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Vediakova, AO & Vedyakov, AA 2020, Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements. in V Sukhomlin & E Zubareva (eds), Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 1140 CCIS, Springer Nature, pp. 251-260, 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018, Moscow, Russian Federation, 29/11/18. https://doi.org/10.1007/978-3-030-37436-5_23

APA

Vediakova, A. O., & Vedyakov, A. A. (2020). Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements. In V. Sukhomlin, & E. Zubareva (Eds.), Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers (pp. 251-260). (Communications in Computer and Information Science; Vol. 1140 CCIS). Springer Nature. https://doi.org/10.1007/978-3-030-37436-5_23

Vancouver

Vediakova AO, Vedyakov AA. Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements. In Sukhomlin V, Zubareva E, editors, Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers. Springer Nature. 2020. p. 251-260. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-030-37436-5_23

Author

Vediakova, Anastasiia O. ; Vedyakov, Alexey A. / Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements. Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers. editor / Vladimir Sukhomlin ; Elena Zubareva. Springer Nature, 2020. pp. 251-260 (Communications in Computer and Information Science).

BibTeX

@inproceedings{f8b5a927767d46c18b19d57735026f30,
title = "Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements",
abstract = "This paper is devoted to the rotor angular velocity estimation of the permanent-magnet synchronous motor (PMSM). It is an actual problem, for example, in sensorless control. We consider a classical, two-phase model in the stator frame of the unsaturated, non-salient PMSM in the state-space representation. All parameters of the model except the stator windings resistance and rotor inertia are assumed to be known. On the first step, we find the relation between measured signals and angular velocity and excluding the unknown parameters of the motor. This relation is simplified using properties of the measured signals and represented as the first-order regression model, where the unknown parameter is the angular velocity. On the next step, we propose the estimation scheme, which is based on the gradient descent method. The efficiency is illustrated through a set of numerical simulations.",
keywords = "Parameter identification, Permanent magnet synchronous motor, Real-time, Sensorless control",
author = "Vediakova, {Anastasiia O.} and Vedyakov, {Alexey A.}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018 ; Conference date: 29-11-2018 Through 02-12-2018",
year = "2020",
doi = "10.1007/978-3-030-37436-5_23",
language = "English",
isbn = "9783030374358",
series = "Communications in Computer and Information Science",
publisher = "Springer Nature",
pages = "251--260",
editor = "Vladimir Sukhomlin and Elena Zubareva",
booktitle = "Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers",
address = "Germany",

}

RIS

TY - GEN

T1 - Simplified Rotor Angular Velocity Estimation for a Permanent Magnets Synchronous Motor by Current and Voltage Measurements

AU - Vediakova, Anastasiia O.

AU - Vedyakov, Alexey A.

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - This paper is devoted to the rotor angular velocity estimation of the permanent-magnet synchronous motor (PMSM). It is an actual problem, for example, in sensorless control. We consider a classical, two-phase model in the stator frame of the unsaturated, non-salient PMSM in the state-space representation. All parameters of the model except the stator windings resistance and rotor inertia are assumed to be known. On the first step, we find the relation between measured signals and angular velocity and excluding the unknown parameters of the motor. This relation is simplified using properties of the measured signals and represented as the first-order regression model, where the unknown parameter is the angular velocity. On the next step, we propose the estimation scheme, which is based on the gradient descent method. The efficiency is illustrated through a set of numerical simulations.

AB - This paper is devoted to the rotor angular velocity estimation of the permanent-magnet synchronous motor (PMSM). It is an actual problem, for example, in sensorless control. We consider a classical, two-phase model in the stator frame of the unsaturated, non-salient PMSM in the state-space representation. All parameters of the model except the stator windings resistance and rotor inertia are assumed to be known. On the first step, we find the relation between measured signals and angular velocity and excluding the unknown parameters of the motor. This relation is simplified using properties of the measured signals and represented as the first-order regression model, where the unknown parameter is the angular velocity. On the next step, we propose the estimation scheme, which is based on the gradient descent method. The efficiency is illustrated through a set of numerical simulations.

KW - Parameter identification

KW - Permanent magnet synchronous motor

KW - Real-time

KW - Sensorless control

UR - http://www.scopus.com/inward/record.url?scp=85081049297&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-37436-5_23

DO - 10.1007/978-3-030-37436-5_23

M3 - Conference contribution

AN - SCOPUS:85081049297

SN - 9783030374358

T3 - Communications in Computer and Information Science

SP - 251

EP - 260

BT - Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers

A2 - Sukhomlin, Vladimir

A2 - Zubareva, Elena

PB - Springer Nature

T2 - 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018

Y2 - 29 November 2018 through 2 December 2018

ER -

ID: 76547418