Issue |
MATEC Web Conf.
Volume 329, 2020
International Conference on Modern Trends in Manufacturing Technologies and Equipment: Mechanical Engineering and Materials Science (ICMTMTE 2020)
|
|
---|---|---|
Article Number | 03071 | |
Number of page(s) | 9 | |
Section | Mechanical Engineering | |
DOI | https://doi.org/10.1051/matecconf/202032903071 | |
Published online | 26 November 2020 |
Digital twin of mechatronic drive based on the optimal control model of BLDC motor
1 Department of Mechatronic Systems, Kalashnikov Izhevsk State Technical University, 426069, Studencheskaya str, 7, Izhevsk, Russia
* Corresponding author: trefilov376908@gmail.com
This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.