Performance enhancement of brushless direct current motor under different novel optimization techniques

Abstract

This research paper presents a novel attempt of speed control for brushless direct current (BLDC) motor in low power/servo motor applications. The performance is measured based on the swiftness for the recovery of desired speed amidst in disturbances, sensitive to supply/motor load fluctuations. The proportional integral (PI) controller is competent only for linear time invariant systems. The state of art technology is, PI controller is used with metaheuristic optimization algorithms viz. Honeybee mating optimization (HBO), artificial immune system (AIS), and frog leaping guided algorithm (FLG), for fine tuning of gain coefficients. Earlier literature survey shows power quality and time domain specifications for separate applications. An innovative approach for the assessment of performance indicators like maximum overshoot (M_p), settling time (t_s), power factor (PF) and total harmonic distortion (THD) simultaneously in the optimized PI controller is suggested. By avoiding local optima trapping, this method gives better dynamic performance for various test conditions. MATLAB/Simulink 2021a software is utilized in the examination of performance in various load and speed scenarios, subsequently validated with hardware where cost effective Arduino controller replaced programmable interface controllers (PIC) microcontroller.