Control of the HIV Infection Dynamics with a Reduced Second Order Model

The HIV infection is a dynamic process that can be modeled mathematically. By means of changing the drug effect in the model, the primary goal of this paper is to show how to drive any initial state into an equilibrium called the nonprogressor, where the infected patient does not develop symptoms of AIDS. The goal is achieved by a new method of treatment. This method is based on an approximation of higher order dynamics by a reduced order model. For the approximation, we divide the HIV infection model into two subsystems and modify one of the subsystems to emulate the whole system. With the modification, we relieve the load to deal with the high order model, such as state observation and parameter estimation. The effectiveness of the new treatment is demonstrated by computer simulations.