Design of a fuzzy-based proportional integral derivative controller with optimal membership function scaling for respiratory ventilation system

In this paper, an optimum membership function based fuzzy proportional integral derivative (Fuzzy-PID) controller is proposed to improve the pressure tracking profile of pressure controlled ventilator (PCV) system. A PCV structure as a respiratory support system is spatially designed for seated patients with homogenous lung system. During anesthesia procedure, such type of ventilator is used. For the comfort and safety of patients, the airway pressure of such device must exactly track the desired pressure of patients. As, PID based control structure is well accepted in industry due to the simple structure, easy implementation and efficiency to work robustly. Therefore, a Fuzzy-PID control structure is considered for PCV system. The fuzzy concept is used to tune the parameters of the PID controller. The novelty of the present work is that the membership function of fuzzy inputs (error and change in error in terms of airway pressure) and the outputs (parameters of the PID controller) are optimized with a swarm based optimizer. Therefore, a boosted class topper optimization (BCTO) algorithm is developed. With the proposed control scheme, the presser tracking profile of PCV system is improved in terms of response time, settling time and overshoot and compared with existing one.