Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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.
Original language | English |
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Title of host publication | Convergent Cognitive Information Technologies - 3rd International Conference, Convergent 2018, Revised Selected Papers |
Editors | Vladimir Sukhomlin, Elena Zubareva |
Publisher | Springer Nature |
Pages | 251-260 |
Number of pages | 10 |
ISBN (Print) | 9783030374358 |
DOIs | |
State | Published - 2020 |
Event | 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018 - Moscow, Russian Federation Duration: 29 Nov 2018 → 2 Dec 2018 |
Name | Communications in Computer and Information Science |
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Volume | 1140 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference | 3rd International Scientific Conference on Convergent Cognitive Information Technologies, Convergent 2018 |
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Country/Territory | Russian Federation |
City | Moscow |
Period | 29/11/18 → 2/12/18 |
ID: 76547418