Online neural network application for compensation of the VSI voltage nonlinearities

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F23%3APU149634" target="_blank" >RIV/00216305:26620/23:PU149634 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10312305" target="_blank" >https://ieeexplore.ieee.org/document/10312305</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IECON51785.2023.10312305" target="_blank" >10.1109/IECON51785.2023.10312305</a>

Result language
angličtina
Original language name
Online neural network application for compensation of the VSI voltage nonlinearities
Original language description
The paper aims to solve the distortion problem of the inverter output voltages that cause harmonic deformation of the phase currents and ripple of dq- currents of the three-phase permanent magnet synchronous motor (PMSM). The inverter non-linearities adversely affect the effectiveness of the PMSM control algorithm. The compensation strategy is based on the neural network and knowledge of the three-phase PMSM model structure and its parameters. The input data for the neural network consist of the normed values and detected polarities of the phase currents and rotor position information. As a result, the proposed artificial neural network (ANN) can extract non-linear functions from the measured data to compensate for the VSI output voltages. The ANN is designed to learn online while the PMSM is running. The back-propagation algorithm is used for neural network learning. The proposed stratégy was implemented in an AURIX TC397 microcontroller and validated by experiments on a real PMSM. The presented results demonstrate the effectiveness of the proposed solution.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
ISBN
979-8-3503-3182-0
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
Singapur
Event location
Singapore
Event date
Oct 16, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)