Artificial neural network motor control for full-electric injection moulding machine

Vagapov, Yuriy, Veligorskyi, Oleksandr, Chakirov, Roustiam and Khomenko, Maksym (2019) Artificial neural network motor control for full-electric injection moulding machine. In: IEEE International Conference on Industrial Technology, 13-15 February 2019, Melbourne, Australia.

[img]
Preview
Text
GURO_401_PID5702225.pdf - Accepted Version

Download (1MB) | Preview

Abstract

This paper proposes a new artificial neural network-based position controller for a full-electric injection moulding machine. Such a controller improves the dynamic characteristics of the positioning for hot runners, pin valve and the injection motors for varying moulding parameters. Practical experimental data and Matlab’s System Identification Toolbox have been used to identify the transfer functions of the motors. The structure of the artificial neural network, which used positioning error and speed of error, was obtained by numerical modelling in Matlab/Simulink. The artificial neural network was trained using back-propagation algorithms to provide control of the motor current thus ensuring the required position and velocity. The efficiency of the proposed ANN-based controller has been estimated and verified in Simulink using real velocity data and the position of the injection moulding machine and pin valve motors.

Item Type: Conference or Workshop Item (Paper)
Keywords: injection moulding, motor drive, permanent magnet motors, brushless motors, artificial neural networks, control
Divisions: Applied Science, Computing and Engineering
Depositing User: Hayley Dennis
Date Deposited: 06 Aug 2019 11:42
Last Modified: 06 Aug 2019 11:42
URI: http://glyndwr.repository.guildhe.ac.uk/id/eprint/17455

Actions (login required)

Edit Item Edit Item