DOI

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.

Язык оригиналаанглийский
Название основной публикацииConvergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers
РедакторыVladimir Sukhomlin, Elena Zubareva
ИздательSpringer Nature
Страницы251-260
Число страниц10
ISBN (печатное издание)9783030374358
DOI
СостояниеОпубликовано - 2020
Событие3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018 - Moscow, Российская Федерация
Продолжительность: 29 ноя 20182 дек 2018

Серия публикаций

НазваниеCommunications in Computer and Information Science
Том1140 CCIS
ISSN (печатное издание)1865-0929
ISSN (электронное издание)1865-0937

конференция

конференция3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018
Страна/TерриторияРоссийская Федерация
ГородMoscow
Период29/11/182/12/18

    Предметные области Scopus

  • Компьютерные науки (все)
  • Математика (все)

ID: 76547418