An Observer for Mass-action Chemical Reaction Networks

M. Farina, S. Bittanti
{"title":"An Observer for Mass-action Chemical Reaction Networks","authors":"M. Farina, S. Bittanti","doi":"10.3166/ejc.15.578-593","DOIUrl":null,"url":null,"abstract":"In biological research, experimental data analysis plays an important role since it enables quantitative understanding of biochemical processes. On the other hand, today's measurement techniques, in continuous development, generally allow measuring a subset of the major system's variables. Such major issue can be tackled by relying on a system's and mathematical approach. For instance, first principles modelling of metabolic or signal transduction networks typically leads to a set of nonlinear differential equations. In this paper, we devise a nonlinear observer specifically suited for models of biochemical reaction networks. We show that the observer is locally convergent under certain observability conditions which can be inferred by elementary network analysis. The applicability and performance of the outlined observer are shown considering the state estimation problem for a benchmark biochemical reaction network.","PeriodicalId":11813,"journal":{"name":"Eur. J. Control","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eur. J. Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3166/ejc.15.578-593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

In biological research, experimental data analysis plays an important role since it enables quantitative understanding of biochemical processes. On the other hand, today's measurement techniques, in continuous development, generally allow measuring a subset of the major system's variables. Such major issue can be tackled by relying on a system's and mathematical approach. For instance, first principles modelling of metabolic or signal transduction networks typically leads to a set of nonlinear differential equations. In this paper, we devise a nonlinear observer specifically suited for models of biochemical reaction networks. We show that the observer is locally convergent under certain observability conditions which can be inferred by elementary network analysis. The applicability and performance of the outlined observer are shown considering the state estimation problem for a benchmark biochemical reaction network.
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
质量作用化学反应网络的观察者
在生物学研究中,实验数据分析起着重要的作用,因为它可以定量地了解生化过程。另一方面,今天的测量技术,在持续发展中,通常允许测量主要系统变量的子集。这样的重大问题可以依靠系统和数学方法来解决。例如,代谢或信号转导网络的第一性原理建模通常会导致一组非线性微分方程。在本文中,我们设计了一个非线性观测器,特别适合于生化反应网络模型。在一定的可观测性条件下,我们证明了观测器是局部收敛的。针对一个基准生化反应网络的状态估计问题,说明了所提观测器的适用性和性能。
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
自引率
0.00%
发文量
0
期刊最新文献
Nonlinear model predictive control for thermal balance in solar trough plants Model reference adaptive control with adjustable gain for piezoelectric actuator Robust non-fragile boundary control for non-linear parabolic PDE systems with semi-Markov switching and input quantization Stabilization of rational nonlinear discrete-time systems by state feedback and static output feedback Experimental study on a novel simultaneous control and identification of a 3-DOF delta robot using model reference adaptive control
×
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