State estimation for delayed genetic regulatory networks with reaction diffusion terms and Markovian jump

被引：0
|
作者：
Chengye Zou
Changjun Zhou
Qiang Zhang
Xinyu He
Chun Huang
机构：
[1] Yanshan University,College of Information Science and Engineering
[2] Anyang Normal University,School of Mathematics and Statistics
[3] Dalian University of Technology,Informedia Electronic Co., Ltd.
[4] Dalian University of Technology,Faculty of Electronic Information and Electrical Engineering
[5] Zhejiang Normal University,School of Computer Science and Technology
[6] Liaoning Normal University,School of Computer and Information Technology
[7] Zhengzhou University of Light Industry,College of Electrical and Electronic Engineering
来源：
Complex & Intelligent Systems | 2023年 / 9卷
关键词：
Genetic regulatory networks; Dirichlet boundary; State estimation; Reaction–diffusion; Markov jumping; Parameter uncertain;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Robust state estimation for delayed genetic regulatory networks with reaction–diffusion terms and uncertainties terms under Dirichlet boundary conditions is addressed in this article. The main purpose of the problem investigation is to design a novel state observer for estimate the true concentrations of mRNA and protein by available measurement outputs. Based on Lyapunov–Krasovskii functions and linear matrix inequalities (LMI), sufficient conditions are given to ensure the robust stability of the estimation error networks. Two examples are presented to illustrate the effectiveness of the proposed approach.
引用
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页码：5297 / 5311
页数：14
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