Filtered model-based predictive control applied to the temperature and humidity control of a neonatal incubator

This paper proposes a robust multivariable predictive control algorithm that improves the robustness of closed loop systems, even when they have multiple time delays between the inputs and outputs. The desired robustness is achieved by including an appropriate filter on the disturbances model. The proposed algorithm is applied to the control of humidity and temperature of a neonatal incubator. Simulation and experimental results show the advantages of the proposed algorithm compared to others proposed in the literature.