High-Gain Estimation of mRNA and Protein Concentrations of a Genetic Regulatory Network

In this paper, we investigate the problem of state estimation for a simple one-gene regulation dynamic process involving end-product activation to rebuild the non-measured concentrations of mRNA and the involved protein. We syn-thesize a convenient observer structure following the high-gain methodology by combining the observer proposed in [1] based on the system state augmentation approach and the HG/LMI technique presented in [2]. The proposed design reduces sig-nificantly the value of the tuning parameter and the observer gain along with improving its sensitivity to disturbances and measurement noise. The results are compared with the standard high-gain observer to evaluate the effectiveness of the proposed design.