Precise oxygen therapy to emphysema patients by fuzzy-based gain tuning control of set-point regulated MRAC

Abstract

Emphysema, a primary component of chronic obstructive pulmonary disease (COPD), causes progressive dyspnea through the destruction of alveolar membranes. This structural degradation reduces the available surface area for gas exchange, significantly impairing oxygen delivery to the bloodstream. While oxygen therapy is a critical intervention, the inherent physiological complexities, specifically transit time delays and dynamic respiratory demands, make precise oxygen regulation exceptionally difficult. To address these challenges, this study develops a comprehensive mathematical model of the emphysema-affected respiratory system, incorporating specific parameters for time delays in oxygen exchange. A novel Intelligent Set-point Modulated Fuzzy Model Reference Adaptive Controller (SFMRAC) is proposed to enhance oxygen regulation. This control architecture advances traditional Model Reference Adaptive Controller (MRAC) by integrating a normalization factor, fuzzy logic tuning, and set-point modulation. This hybrid approach allows the system to adapt to nonlinear physiological variations and maintain stability despite the transit delays characteristic of damaged pulmonary tissue. The effectiveness of the SFMRAC was evaluated through a simulation study conducted in MATLAB/Simulink. Results demonstrate that the proposed controller provides superior tracking performance and robustness compared to MRAC, particularly when subjected to varying set-points and significant exchange delays. The results suggest that the SFMRAC offers a promising computational framework to improve the automated delivery of oxygen therapy in clinical settings for COPD patients.