Pressure and Volume Control of Ventilator Using Fuzzy Logic

Abstract

Precise control is critical in the field of medical ventilator systems to guarantee the best possible care for patients. This study investigates the application of fuzzy logic to control volume and pressure in response to servo motor angle changes. The goal of the project is to show how fuzzy logic can effectively address the uncertainties present in physiological systems by utilising MATLAB's capabilities. The study demonstrates the flexibility and stability of the fuzzy logic technique through extensive simulations and analysis, underscoring its potential to improve ventilator control accuracy. The results point to a viable direction for the development of control techniques in important medical applications that offer a cutting-edge method for improving respiratory support in critical care environments. This study focuses on using fuzzy logic to control the volume and pressure parameters in mechanical ventilators. Fuzzy control techniques are used by the system to dynamically adjust to patient-specific conditions and optimize ventilation depending on feedback received in real-time. The objective of the suggested methodology is to enhance patient outcomes by offering a respiratory support mechanism that is more accurate and flexible. Through simulation and experimental validation, the study explores the viability and effectiveness of the fuzzy logic-based control system, highlighting its potential to improve ventilator performance and provide individualized and responsive critical care. By bridging the gap between sophisticated control systems and traditional ventilation procedures, this research presents a possible path forward for respiratory therapy breakthroughs.