Key result
A set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) was developed and simulated to instantly react to changes in oxygen demand in patients with respiratory distress.
Why the study?
Controlled oxygen supply is critical for severe respiratory distress, but existing conventional and intelligent controllers have limitations in reacting instantly to changes in patient oxygen demand.
Does a set-point modulated fuzzy PI-based model reference adaptive controller improve oxygen supply regulation in simulated models of severe respiratory distress?
Does a set-point modulated fuzzy PI-based model reference adaptive controller improve oxygen supply regulation in simulated models of severe respiratory distress?
A novel fuzzy PI-based adaptive controller demonstrates theoretical efficacy in regulating oxygen supply for simulated respiratory distress models.
May support refined oxygen protocols in respiratory failure; leaves open validation in prospective diagnostics studies.
Uncontrolled breathing is the most critical and challenging situation for a healthcare person to patients. It may be due to simple cough/cold/critical disease to severe respiratory infection of the patients and resulting directly impacts the lungs and damages the alveoli which leads to shortness of breath and also impairs the oxygen exchange. The prolonged respiratory failure in such patients may cause death. In this condition, supportive care of the patients by medicine and a controlled oxygen supply is only the emergency treatment. In this paper, as a part of emergency support, the intelligent set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) is delineated to control the oxygen supply to uncomforted breathing or respiratory infected patients. The effectiveness of the model reference adaptive controller (MRAC) is enhanced by assimilating the worthiness of fuzzy-based tuning and set-point modulation strategies. Since then, different conventional and intelligent controllers have attempted to regulate the supply of oxygen to respiratory distress patients. To overcome the limitations of previous techniques, researchers created the set-point modulated fuzzy PI-based model reference adaptive controller, which can react instantly to changes in oxygen demand in patients. Nonlinear mathematical formulations of the respiratory system and the exchange of oxygen with time delay are modeled and simulated for study. The efficacy of the proposed SFPIMRAC is tested, with transport delay and set-point variations in the devised respiratory model.
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Naskar et al. (2023) studied Severe respiratory distress. Set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) was evaluated on Efficacy of the proposed SFPIMRAC with transport delay and set-point variations in the devised respiratory model. A set-point modulated fuzzy PI-based model reference adaptive controller (SFPIMRAC) was developed and simulated to instantly react to changes in oxygen demand in patients with respiratory distress.
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