State Feedback and Synergetic controllers for tuberculosis in infected population.

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2021-05-01 Epub Date: 2021-03-30 DOI:10.1049/syb2.12013
Muhammad Bilal, Iftikhar Ahmad, Sheraz Ahmad Babar, Khurram Shahzad
{"title":"State Feedback and Synergetic controllers for tuberculosis in infected population.","authors":"Muhammad Bilal,&nbsp;Iftikhar Ahmad,&nbsp;Sheraz Ahmad Babar,&nbsp;Khurram Shahzad","doi":"10.1049/syb2.12013","DOIUrl":null,"url":null,"abstract":"<p><p>Tuberculosis (TB) is a contagious disease which can easily be disseminated in a society. A five state Susceptible, exposed, infected, recovered and resistant (SEIRs) epidemiological mathematical model of TB has been considered along with two non-linear controllers: State Feedback (SFB) and Synergetic controllers have been designed for the control and prevention of the TB in a population. Using the proposed controllers, the infected individuals have been reduced/controlled via treatment, and susceptible individuals have been prevented from the disease via vaccination. A mathematical analysis has been carried out to prove the asymptotic stability of proposed controllers by invoking the Lyapunov control theory. Simulation results using MATLAB/Simulink manifest that the non-linear controllers show fast convergence of the system states to their respective desired levels. Comparison shows that proposed SFB controller performs better than Synergetic controller in terms of convergence time, steady state error and oscillations.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675849/pdf/","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1049/syb2.12013","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/3/30 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 2

Abstract

Tuberculosis (TB) is a contagious disease which can easily be disseminated in a society. A five state Susceptible, exposed, infected, recovered and resistant (SEIRs) epidemiological mathematical model of TB has been considered along with two non-linear controllers: State Feedback (SFB) and Synergetic controllers have been designed for the control and prevention of the TB in a population. Using the proposed controllers, the infected individuals have been reduced/controlled via treatment, and susceptible individuals have been prevented from the disease via vaccination. A mathematical analysis has been carried out to prove the asymptotic stability of proposed controllers by invoking the Lyapunov control theory. Simulation results using MATLAB/Simulink manifest that the non-linear controllers show fast convergence of the system states to their respective desired levels. Comparison shows that proposed SFB controller performs better than Synergetic controller in terms of convergence time, steady state error and oscillations.

Abstract Image

Abstract Image

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
感染人群结核病的状态反馈和协同控制。
结核病是一种容易在社会中传播的传染病。建立了结核病易感、暴露、感染、恢复和耐药(seir)五状态流行病学数学模型,并设计了两种非线性控制器:状态反馈(SFB)和协同控制器,用于人群结核病的控制和预防。使用拟议的控制器,通过治疗减少/控制了受感染个体,并通过接种疫苗预防了易感个体感染该疾病。通过引用李雅普诺夫控制理论,对所提出的控制器的渐近稳定性进行了数学分析。利用MATLAB/Simulink进行的仿真结果表明,非线性控制器能够快速地将系统状态收敛到期望的水平。结果表明,所提出的SFB控制器在收敛时间、稳态误差和振荡方面都优于协同控制器。
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 Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
期刊最新文献
iGATTLDA: Integrative graph attention and transformer-based model for predicting lncRNA-Disease associations. A tumour-associated macrophage-based signature for deciphering prognosis and immunotherapy response in prostate cancer. Identification and analysis of epithelial-mesenchymal transition-related key long non-coding RNAs in hypospadias Revealing the potential role of hub metabolism-related genes and their correlation with immune cells in acute ischemic stroke Gene signatures of endoplasmic reticulum stress and mitophagy for prognostic risk prediction in lung adenocarcinoma
×
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