A Genetic-Fuzzy System Approach to Control a Model of the HIV Infection Dynamics

This paper presents a genetic fuzzy system approach to control a nonlinear dynamic model of the HIV infection. The system is conceived to find mamdani fuzzy controllers that are capable of boosting the immune response while reducing the impact on the body because of the use of potentially toxic medicaments. General aspects of the used approach are described while special emphasis is given to the evolutionary mechanism. The best solution found from several evolutionary runs is analyzed in terms of control and interpretability issues.

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