Closed-Loop Ventilation of Oxygenation and End-Tidal CO2

For a clinical application, oxygenation and etCO₂ are required to be regulated to a specific value for minimizing the risk of hypoxia and hypercapnia or hypocapnia. To realize these tasks, a knowledge-based controller, a fuzzy controller and a model-based H_∞ controller are proposed in this article for controlling the complex nonlinear cardiopulmonary system. The selection of controlled variables is critical for each control objective: PEEP and FiO₂ for oxygenation and minute ventilation (MV) for etCO₂. In this article, the new and concrete results of animal experiments are presented for a knowledge-based controller and a fuzzy controller. In addition, a model-based approach using H_∞ loop-shaping technique is proposed for the control of etCO₂ as a pilot study. System identification is carried out to determine the model structure of the porcine dynamics. Based on a numerical study, the second order system with one zero describes the system with the best RMSE criteria, corresponding to the model obtained by human models. Based on the simulation result, the model-based H_∞ loop-shaping technique is a distinguished approach for the control of etCO₂.