An enhanced human conception optimization algorithm based optimal 2-DoF-PID controller for Artificial Respiratory Ventilation System

Artificial ventilator is generally utilized in critical care units (ICUs) or anaesthesia workstations to provide critically ill patients with respiratory support. They are operated in pressure control mode, volume control mode, or both. Dyssynchrony between the patient and the artificial ventilator is one of the most critical issues. There is a mismatch between a patient's respiratory system's timing, the flow, volume, or pressure that is needed, and a ventilator's capacity to fulfil those needs during ventilation. Negative effects of patient-ventilator dyssynchrony include patient annoyance, alveolar overdistention and lung injury, sleep issues, erratic breathing, excessive unconsciousness, and overloading of the diaphragm leading to ventilator-induced diaphragmatic malfunction. In this paper, the pressure tracking response of a patient-hose blower-driven pressure controlled ventilator is improved with an optimal two degree of freedom proportional-integral-differential (2-DOF-PID) controller. An enhanced human conception optimization algorithm is developed to optimize the parameters of the controller for the ventilator model. The robustness and accuracy of the proposed controller for the ventilator model are examined under different scenarios and compared with existing results.