ANFIS Based Hybrid Sensorless Speed Control Technique for BLDC Motor

Abstract

Brushless Direct Current (BLDC) motor has emerged as one of the efficient alternative for conventional motors. Speed control is an essential component in the smooth and effective operation of the BLDC motor. In this paper, an intelligent sensorless speed control technique based on Artificial Neural Network (ANN) and Adaptive Network-based Fuzzy Inference System (ANFIS) is proposed. The back EMF of the motor is measured and ANFIS is used to generate Hall signals based on back EMF. ANN is then used to develop pulses required for the three phase inverter; this avoids use of logic gate circuits for pulse generation. PI controller is used to control the input DC voltage given to the inverter. The proposed method is implemented using MATLAB/SIMULINK and the results are analyzed. The results show effectiveness of the proposed method in controlling the speed of BLDC motor.