Tuning of Fractional Order Proportional Integral Derivative Controller for Speed Control of Sensorless BLDC Motor using Artificial Bee Colony Optimization Technique

Abstract

This paper introduces a novel method based on the artificial bee colony (ABC) presented for optimal tuning fractional-order proportional–integral–derivative (FOPID) controller for speed control of sensorless brushless direct current (BLDC) motor which can guarantee the desired speed control and the robustness of the closed-loop system. ABC algorithm is a recently proposed global search optimization technique which simulates the behavior of natural bees for determining the optimal parameter values. The proposed method minimizes the steady-state and transient response, i.e., steady-state error, peak overshoot time, rise time, peak time, and settling time with the help of ABC optimal tuning five-degree parameters K p , K i , K d , λ, and μ. In addition, the comparative study has been made to analyze the step response characteristics of BLDC motor drive using ABC over come conventional genetic algorithm (GA) for speed regulation of the motor. MATLAB simulation and extensive analysis of results obtained show the effectiveness of the proposed approach.