en Stochastic Control Stochastic Control Research Paper Research Paper <p>Artificially regulating gene expression is an important step in developing new<br> treatment for system-level disease such as cancer. In this paper, we propose a method to<br> regulate gene expression based on sampled-data measurements of gene products<br> concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with<br> stochastic nonlinear differential equation. To synthesize feedback controller, we formulate<br> sampling process as an impulsive system. By using a new Lyapunov function with<br> discontinuities at sampling times, state feedback gain that guarantees exponential meansquare<br> stability and H&infin performance is derived from LMIs. These LMIs also determine the<br> maximum allowable time between sampling points. A numerical example and a practical<br> application are presented to justify the applicability of the theoretical results</p> <p style="text-align: left;"><img alt="AWT IMAGE" src="./files/site1/images/3.png" style="width: 250px; height: 250px;" ></p> Gene Regulatory Networks,Impulsive Systems,Linear Matrix Inequality,Sampled-Data Control, 204 216 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-192-1&slc_lang=en&sid=1 M. Mohammadian m.mohammadiankebria@gmail.com 180031947532846003761 180031947532846003761 No Tarbiat Modares University H. R. Momeni momeni_h@modares.ac.ir 180031947532846003762 180031947532846003762 Yes Tarbiat Modares University M. Tahmasebi tahmasebi@modares.ac.ir 180031947532846003763 180031947532846003763 No Tarbiat Modares University