Feedback control of an HBV Model based on differential evolution and Kalman filter

초록

In this talk, we investigate viral dynamics of hepatitis B using a mathematical model which is in the form of a system of ordinary differential equations. We show that the proposed model has one virus-free steady state and a chronic steady state. We conduct a local stability analysis of these steady states based on the basic reproduction number. A model predictive control (MPC) based on the differential evolution (DE) method is proposed to design (sub)optimal treatment regimes. In addition, the problem of implementing the DE methodology and the extended Kalman filter (EKF) with inaccurate or incomplete observation data and long measurement periods is addressed. Numerical results indicate the effects of two types of dynamic treatments representing reverse transcriptase (RT) inhibitors and protease inhibitors (PIs) in minimizing both the virus population and infected cells. CJK-K1