Sensorless Firefly Algorithm for Speed Control of BLDC Motors

• Published in: 2022 5th International Conference on Contemporary Computing and Informatics (IC3I) pp. 1538 - 1543
• Main Authors: Pandya, Dharmesh J., Singh, Akanksha, VinothKumar, T., Raturi, Anuj, Deepak, A., Khan, Irfan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.12.2022
• Subjects: BLDC motor; Brushless DC motors; Firefly Algorithm; Heuristic algorithms; PID controller; Rotors; Sensorless control; Software; Torque; Velocity control
• DOI: 10.1109/IC3I56241.2022.10072541

The speed of a brushless direct current (BLDC) motor can be controlled in a way inspired by the workings of the natural world. To obtain the best proportional integral (PID) derivative parameters that also produce the lowest possible value for the time domain objective function, the proposed speed controller design is reformatted as a optimization challenge and the firefly FFA algorithm used. Population-based algorithms have many advantages over traditional methods when it comes to solving difficult optimization problems. The proposed FFA-PID controller's performance has been assessed for sudden changes in setpoint, load torque at speeds below rated speed, and rated speed in comparison to rated speed. A brushless DC motor's drive is simulated using the MATLAB/SIMULINK software suite. The simulation outcomes demonstrate that the proposed method outperforms the artificial bee colony method in terms of controlling the engine's operating speed when the particular time domain parameters are altered. FOPID and PID controllers were contrasted in this proposal using the artificial swarm method and the firefly technology. The firefly and artificial bee algorithms for choosing the right PID parameters to drive a brushless DC motor. After comparing a wide range of controllers and algorithms, we came to the conclusion that the PID controller will function best in hardware.