Model-Based Flow Rate Control with Online Model Parameters Identification in Automatic Pouring Machine

Author:

Kabasawa Nobutoshi,Noda YoshiyukiORCID

Abstract

In this study, we proposed an advanced control system for tilting-ladle-type automatic pouring machines in the casting industry. Automatic pouring machines have been introduced recently to improve the working environment of the pouring process. In the conventional study on pouring control, it has been confirmed that the pouring flow rate control contributes to improving the accuracy of the entire automatic pouring machine, such as the outflow liquid’s falling position from the ladle, the liquid’s weight filled in the mold, and the sprue cup’s liquid level. However, the conventional control system has problems: it is not easy to precisely pour the liquid in the ladle with a large tilting angle, and it takes time to adjust the control parameters. Therefore, we proposed the feedforward pouring flow rate control system, constructed by the pouring process’ inverse model with the online model parameters identification. In this approach, we derived the pouring process’ mathematical model, representing precisely the pouring process with the ladle’s large tilting angle. The model parameters in the pouring process’ inverse model in the controller are updated online via the model parameters identification. To verify the proposed pouring control system’s efficacy, we experimented using the tilting-ladle-type automatic pouring machine. In the experimental results, the mean absolute error between the outflow liquid’s weight and the reference weight was improved from 0.1346 at the first pouring to 0.0498 at the fifth pouring. Moreover, the model parameters were identified within 4 s. Therefore, it enables updating the controller’s parameters within each pouring motion interval by the proposed approach.

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Publisher

MDPI AG

Subject

Artificial Intelligence,Control and Optimization,Mechanical Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Development of Automated Control System for Laboratory Reactoplast Casting Unit;2024 4th International Conference on Technology Enhanced Learning in Higher Education (TELE);2024-06-20

2. The edge extraction method of casting images based on improved Canny operator;2022 IEEE International Conference on Mechatronics and Automation (ICMA);2022-08-07

3. Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine;Applied Sciences;2021-07-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3