Monitoring and optimization of speed settings for Brushless Direct Current (BLDC) using Particle Swarm Optimization (PSO)

Abstract

This paper presents the setting of the speed of a motor Brushless Direct Current (BLDC) optimized by artificial intelligence. It discusses the comparison between the speed setting of BLDC motor optimized by Particle Swarm Optimization (PSO) and without optimization. The finding shows that the performance of the BLDC motor speed setting optimized by PSO algorithm provides optimal value for the proportional gain constant of 27.0384, integral gain of 5.1108, integral derivatives of 1.9394 and smaller errors of 2,835. In short, the use of PSO algorithm can speed up the stability and reduce the errors.