Finite-time state observer for delayed reaction-diffusion genetic regulatory networks

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• 作者：Xiaofei Fan ^{2141037@s.hlju.edu.cn}Author Vitae ; Yu Xue ^{xueyu@hlju.edu.cn}Author Vitae ; Xian Zhang ; ^{xianzhang@hlju.edu.cn}Author Vitae ; Jing Ma ^{majing@hlju.edu.cn}Author Vitae
• 关键词：Delayed reaction-diffusion genetic regulatory networks (DRDGRNs) ; Finite-time state observer
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：1 March 2017
• 年：2017
• 卷：227
• 期：Complete
• 页码：18-28
• 全文大小：816 K
• 卷排序：227

文摘

This paper focus on the finite-time state estimation problem for delayed reaction-diffusion genetic regulatory networks (DRDGRNs) under Dirichlet boundary conditions. The purpose is to design a finite-time state observer which is used to estimate the concentrations of mRNAs and proteins via available measurement outputs. By constructing a Lyapunov–Krasovskii functional (LKF) concluding quad-slope integrations, we establish a reaction-diffusion-dependent and delay-dependent finite-time stability criterion for the error system. The derivative of LKF is estimated by employing the Wirtinger-type integral inequality, Gronwall inequality and convex (reciprocally convex) technique. The stability criterion is to check the feasibility of a set of linear matrix inequalities (LMIs), which can be easily realized by the toolbox YALMIP of MATLAB. In addition, the expected finite-time state observer gain matrices can be represented by a feasible solution of the set of LMIs. Finally, two numerical examples are presented to illustrate the effectiveness of the theoretical results.