Design of Genetic Algorithm Based Fractional Order PID Speed Control of Brushless DC Motor In Sleep Apnea Machine

Abstract

The interest in sensor less three-phase BLDC motor for medical applications has been growing in recent years due to their potential advantages over other electric motors. The most popular form of treatment for those who have sleep apnea is the use of a continuous positive airway pressure (CPAP) machine, which keeps the patient's airway open while they sleep by forcing pressurized air down their throat. According to the patient's breathing pattern, the motor's blower fan or rotor speed will, in this application, increase or decrease the patient's airway pressure. This paper presents a unique methodology for sensor-less BLDC motors in CPAP device. The BEMF observer method enables high performance within line-to-line back emf estimation using unknown input because the relationship between magnitude of BEMF and rotor speed is directly proportional. For control of the motor genetic algorithm FOPID and FPID speed controller is implemented to adjust DC-link voltage based on the error between estimated rotor speed and desired speed reference. The controlled gain output of the FOPID and FPID controller is fed to the hysteresis current controlled DC-link voltage source inverter. The result of the FOPID controller has good performance is investigated and the speed of the motor for different speed level using MATLAB/Simulink software. And the result of the simulated speed response of the controller for different speed has been done and settling time is 0.1610sec and rise time is 0.2033sec speed response controller. switching of three-phase voltage source inverter controlled has been done effectively based on the BEMF observer and hysteresis. The simulation results obtained agree with the design objective.