全电动注塑机的人工神经网络电机控制

Oleksandr Veligorskyi, R. Chakirov, M. Khomenko, Y. Vagapov
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引用次数: 5

摘要

本文提出了一种基于人工神经网络的全电动注塑机位置控制器。该控制器改善了热流道、销阀和注射电机在不同成型参数下定位的动态特性。利用实际实验数据和Matlab系统识别工具箱对电机的传递函数进行了识别。利用Matlab/Simulink进行数值模拟,得到了考虑定位误差和误差速度的人工神经网络结构。利用反向传播算法对人工神经网络进行训练,以控制电机电流,从而确保所需的位置和速度。利用注塑机和销阀电机的实际速度数据和位置,在Simulink中对所提出的基于人工神经网络的控制器的效率进行了估计和验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Neural Network Motor Control for Full-Electric Injection Moulding Machine
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.
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