Adaptive control of a pressure-controlled artificial ventilator: A simulator-based evaluation using real COPD patient data

Abstract

The paper discusses the application of a direct adaptive controller to a pressure controlled artificial ventilation problem. In pressure controlled ventilators, the manipulated variable is the maximum flow applied to the patient during the active phase (inspiration), and the regulated variable is the peak pressure at end-inspiration. This simulation case study focuses on patients diagnosed with Chronic Obstructive Pulmonary Disease (COPD), which require artificial/mechanical ventilation. An adaptive PID controller ensures peak pressures below critical values, by manipulating the flow delivered by the ventilator. The simulation study is performed on fractional-order models of the respiratory impedance identified from lung function data obtained from 21 COPD patients. Additional simulation studies show the robustness of the controller in presence of varying model parameters from the respiratory impedance of the patient. Possibilities to implement the control strategy as an online adaptive algorithm are also explored. The results show that the design of the control is suitable for this kind of application and provides useful insight on realistic scenarios.