| Issue |
MATEC Web Conf.
Volume 232, 2018
2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|
|
|---|---|---|
| Article Number | 04040 | |
| Number of page(s) | 4 | |
| Section | Circuit Simulation, Electric Modules and Displacement Sensor | |
| DOI | https://doi.org/10.1051/matecconf/201823204040 | |
| Published online | 19 November 2018 | |
Research and Simulation of Electromagnetic Voltage-Regulated Soft Starter Based on Predictive Control
WenHua College, Wuhan 430074, Hubei Province, China
* Corresponding author: Chen Xiaoling: 359255862@qq.com
Aiming at the problems of large starting current and unsmooth starting of asynchronous motor, an electromagnetic voltage-regulated soft start control method based on predictive control is proposed. The model of motor soft starter based on predictive control algorithm is established. The control principle of predictive control algorithm is analyzed. The CARIMA model is used to adjust the parameters of motor starting process. With the help of MATLAB, the motor direct start model, the electromagnetic control soft starter model based on PID control algorithm and predictive control algorithm are simulated. The results show that the starting current waveform of the electromagnetic voltage regulator soft starter based on the predictive control algorithm is relatively flat, and the control algorithm can achieve a smooth start of the motor.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/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.