Model predictive control for a multi-compartment respiratory system

In this paper, we develop a model predictive controller for a multi-compartment respiratory system. Specifically, for a given periodic reference volume pattern, we design a tracking controller using a framework that merges repetitive control and model predictive control. In particular, the periodic multi-compartment model is transformed into a lifted run-to-run invariant model and a model predictive controller with nonnegative control input constraints is designed. The proposed tracking control framework is applied to a two-compartment lung mechanics model to demonstrate the efficacy of the proposed approach.