Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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. ред. / Vladimir Sukhomlin; Elena Zubareva. Springer Nature, 2020. стр. 251-260 (Communications in Computer and Information Science; Том 1140 CCIS).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
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