摘要：AbstractSeasonal and pandemic influenza A virus (IAV) infections are responsible for critical worldwide morbidity and mortality. In this work, we propose two control techniques to treat the infection at variable time. The first is an off-line approach that considers the differential evolution (DE) algorithm. The second is an on-line approach, which is a combination of model predictive control (MPC) with the DE algorithm. Both approaches determine the best combination of drug-intake times that maximize the virological efficacy index while minimizing the amount of drug applied during the overall treatment period. Numerical results show that both, the MPC-based and the DE-based treatments, reduce the amount of drug administrated and provide similar virological efficacy indices respect to current clinical recommendations.
