Iranian Journal of Electrical and Electronic Engineering

Artificially regulating gene expression is an important step in developing new
treatment for system-level disease such as cancer. In this paper, we propose a method to
regulate gene expression based on sampled-data measurements of gene products
concentrations. Inherent noisy behaviour of Gene regulatory networks are modeled with
stochastic nonlinear differential equation. To synthesize feedback controller, we formulate
sampling process as an impulsive system. By using a new Lyapunov function with
discontinuities at sampling times, state feedback gain that guarantees exponential meansquare
stability and H&infin performance is derived from LMIs. These LMIs also determine the
maximum allowable time between sampling points. A numerical example and a practical
application are presented to justify the applicability of the theoretical results