Optimization of material handling at the automatic warehouse based on the adaptive control algorithm

S. Kruglov, S. Kovyrshin, N. S. Kovaleva
{"title":"Optimization of material handling at the automatic warehouse based on the adaptive control algorithm","authors":"S. Kruglov, S. Kovyrshin, N. S. Kovaleva","doi":"10.1109/ICIEAM.2017.8076192","DOIUrl":null,"url":null,"abstract":"The paper presents an option for automation of the operational procedure at the concentrating coal factory by means of new methods and control algorithms. A crane control automatic system allows choosing the best possible motion trajectories for fast material handling operations and, regardless of processing and disturbing factors, controlling the dynamic state of the handled load which makes material handling significantly more efficient. This automation option implies “examining” of the warehouse surface and automatic choice of the crane motion algorithm. This algorithm takes into account the height of magnetite bulk and ensures fastest possible material handling. To move load to a specified distance without its swinging under prior load mass uncertainty, rope length, external uncontrolled disturbances (friction, wind load), it is proposed to build an adaptive control system with an identification algorithm and an implicit reference model using “simplified” adaptation conditions. The article contains an example demonstrating the efficiency of the proposed approach.)","PeriodicalId":428982,"journal":{"name":"2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEAM.2017.8076192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The paper presents an option for automation of the operational procedure at the concentrating coal factory by means of new methods and control algorithms. A crane control automatic system allows choosing the best possible motion trajectories for fast material handling operations and, regardless of processing and disturbing factors, controlling the dynamic state of the handled load which makes material handling significantly more efficient. This automation option implies “examining” of the warehouse surface and automatic choice of the crane motion algorithm. This algorithm takes into account the height of magnetite bulk and ensures fastest possible material handling. To move load to a specified distance without its swinging under prior load mass uncertainty, rope length, external uncontrolled disturbances (friction, wind load), it is proposed to build an adaptive control system with an identification algorithm and an implicit reference model using “simplified” adaptation conditions. The article contains an example demonstrating the efficiency of the proposed approach.)
基于自适应控制算法的自动仓库物料搬运优化
本文提出了用新的方法和控制算法实现选煤厂操作过程自动化的一种选择。起重机控制自动系统可以选择最佳的运动轨迹,以实现快速物料搬运操作,并且无论加工和干扰因素如何,都可以控制所处理负载的动态状态,从而使物料搬运效率大大提高。这个自动化选项意味着“检查”仓库表面和自动选择起重机运动算法。该算法考虑了磁铁矿体的高度,保证了最快的物料处理速度。为了使负载在事前质量不确定性、绳长不确定性、外部非受控扰动(摩擦、风荷载)的情况下不发生摆动,采用“简化”自适应条件,建立了一种带有识别算法和隐式参考模型的自适应控制系统。文章中包含一个例子来证明所提出的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信