Identification and implementation hybrid fuzzy logic and PID controller for speed control of BLDC motor

Abstract

One of the problems in the optimization process in the Brushless Direct Current (BLDC) speed control system is to obtain a mathematical model in the form of a transfer function. The purpose of this study to mathematically model BLDC motors in transfer functions, and optimization using Proportional, Integral and Derivative (PID) controllers, and fuzzy logic to tune PID controller parameters. The first method used is the process of identifying input and output data from the BLDC motor physical system. The input and output data of the test results simulated to form a mathematical model. The mathematical model of BLDC motor used as the basis for carrying out the optimization process with open loop systems, PID controllers, and fuzzy logic. The results of the research on the optimization process of the BLDC motor speed control system with the fuzzy logic methods obtained the best value for rise time value of 1.25 seconds, settling time value of 382.10 seconds, and peak time is 382.2 seconds. With these results, it shows that the fuzzy logic has given a better transient response than the PID controller in increasing optimal stability.