Sampled-data synchronization of singular Markovian jump system: Application to DC motor model

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IET Cyber-Physical Systems: Theory and Applications Pub Date : 2022-10-18 DOI:10.1049/cps2.12039
Linqi Wang, Guoliang Chen, Te Yang, Jianwei Xia
{"title":"Sampled-data synchronization of singular Markovian jump system: Application to DC motor model","authors":"Linqi Wang,&nbsp;Guoliang Chen,&nbsp;Te Yang,&nbsp;Jianwei Xia","doi":"10.1049/cps2.12039","DOIUrl":null,"url":null,"abstract":"<p>Sampled-data synchronization problem for singular Markovian jump systems (SMJSs) subject to aperiodic sampled-data control is investigated. Firstly, via constructing mode-dependent one-sided loop-based Lyapunov functional (LBLF) and two-sided LBLF, two different stochastically admissible conditions are suggested for error SMJSs with aperiodic sampled-data. It is guaranteed that the slave system is stochastically synchronized to the master system on the basis of the proposed stochastically admissible conditions. Secondly, two corresponding mode-dependent aperiodic sampled-data controller design approaches are provided for error SMJSs based on two different conditions, separately. Finally, the validity of these approaches is demonstrated by a direct current (DC) motor model. It also demonstrated that the two-sided LBLF method possesses a larger upper bound of sampled-data period than the one-sided LBLF method.</p>","PeriodicalId":36881,"journal":{"name":"IET Cyber-Physical Systems: Theory and Applications","volume":"7 4","pages":"171-182"},"PeriodicalIF":1.7000,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cps2.12039","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Cyber-Physical Systems: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cps2.12039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Sampled-data synchronization problem for singular Markovian jump systems (SMJSs) subject to aperiodic sampled-data control is investigated. Firstly, via constructing mode-dependent one-sided loop-based Lyapunov functional (LBLF) and two-sided LBLF, two different stochastically admissible conditions are suggested for error SMJSs with aperiodic sampled-data. It is guaranteed that the slave system is stochastically synchronized to the master system on the basis of the proposed stochastically admissible conditions. Secondly, two corresponding mode-dependent aperiodic sampled-data controller design approaches are provided for error SMJSs based on two different conditions, separately. Finally, the validity of these approaches is demonstrated by a direct current (DC) motor model. It also demonstrated that the two-sided LBLF method possesses a larger upper bound of sampled-data period than the one-sided LBLF method.

Abstract Image

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
奇异马尔可夫跳变系统的采样数据同步:在直流电机模型中的应用
研究了非周期采样数据控制下奇异马尔可夫跳变系统的采样数据同步问题。首先,通过构造基于模式相关单侧环的Lyapunov泛函(LBLF)和基于双侧LBLF,提出了具有非周期采样数据的误差smjs的两种不同的随机允许条件;在提出的随机允许条件的基础上,保证从系统随机同步到主系统。其次,分别针对两种不同条件下的误差smjs给出了两种相应的模态相关非周期采样数据控制器设计方法。最后,通过直流电机模型验证了这些方法的有效性。结果还表明,与单侧LBLF方法相比,双侧LBLF方法具有更大的采样周期上界。
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 去求助
来源期刊
IET Cyber-Physical Systems: Theory and Applications
IET Cyber-Physical Systems: Theory and Applications Computer Science-Computer Networks and Communications
CiteScore
5.40
自引率
6.70%
发文量
17
审稿时长
19 weeks
期刊最新文献
Guest Editorial: IoT-based secure health monitoring and tracking through estimated computing SEIR-driven semantic integration framework: Internet of Things-enhanced epidemiological surveillance in COVID-19 outbreaks using recurrent neural networks A machine learning model for Alzheimer's disease prediction Securing the Internet of Medical Things with ECG-based PUF encryption Status, challenges, and promises of data-driven battery lifetime prediction under cyber-physical system context
×
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