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
{"title":"全电动注塑机的人工神经网络电机控制","authors":"Oleksandr Veligorskyi, R. Chakirov, M. Khomenko, Y. Vagapov","doi":"10.1109/ICIT.2019.8755023","DOIUrl":null,"url":null,"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.","PeriodicalId":6701,"journal":{"name":"2019 IEEE International Conference on Industrial Technology (ICIT)","volume":"42 6","pages":"60-65"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Artificial Neural Network Motor Control for Full-Electric Injection Moulding Machine\",\"authors\":\"Oleksandr Veligorskyi, R. Chakirov, M. Khomenko, Y. Vagapov\",\"doi\":\"10.1109/ICIT.2019.8755023\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":6701,\"journal\":{\"name\":\"2019 IEEE International Conference on Industrial Technology (ICIT)\",\"volume\":\"42 6\",\"pages\":\"60-65\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Conference on Industrial Technology (ICIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2019.8755023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Industrial Technology (ICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2019.8755023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Study on the Thermo-oxidative aging Properties of Nano-SiO2 Composites Based on Cross-linked Polyethylene How Social Media Marketing Affect Purchase Intention Through Customer Engagement in Digital Printing Companies Optimization of Path Selection and Code-Coverage in Regression Testing Using Dragonfly Algorithm Development of Security Starting System for Vehicles Based on IoT A study for the implementation of Banking 4.0 in Indonesia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1