Robust Fuzzy controller design for respiratory systems

A respiratory system combines a blower-hose-patient setup with a single lung system featuring nonlinear lung compliance. This paper explores the optimal design of resilient fuzzy control for such systems by integrating a fuzzy algorithm with a sliding mode control approach. The robust fuzzy controller, as proposed, effectively handles the system’s dynamics and remains stable amidst nonlinear changes. It ensures airway flow and maintains peak pressure below critical levels despite uncertainties like hose leakage and varying respiratory effort. The findings show superior performance in reaction time, overshoot, and tracking errors compared to traditional methods. The control mechanism’s parameters rise time, peak value, heave, and settlement values are independently computed, revealing an over 18% improvement in rise time and a more than 44% reduction in settling time. Simulations indicate the robust fuzzy controller outperforms the PID controller, demonstrating its efficacy for respiratory system control.