Hybrid Sensorless Speed Control Technique for BLDC Motor Using ANFIS Automation

Abstract: Brushless Direct Current (BLDC) motors have been shown to be a cost-effective alternative to traditional motors. The smooth and efficient operation of
the BLDC motor is dependent on speed regulation. This research proposes a sensorless intelligent speed control technique for BLDC using an Adaptive Network-based Fuzzy Inference Systems (ANFIS) based Artificial Bee Colony (ABC)
algorithm. The motor’s back EMF is measured, and ANFIS is used to generate
Hall signals. The ABC is then utilized to provide the pulses needed for the
three-phase inverter, avoiding the requirement of logic gate circuits. The input
DC voltage to the inverter is controlled by a PI controller. The Optimized Field
Oriented Control (OFOC) is implemented to control the sensorless BLDC motor.
The proposed method is implemented and the outcomes are analyzed by
MATLAB/SIMULINK and there is no overshoot and has a low settling time
also the steady-state error is deficient than the existing methods. This proposed method can be improved by reducing the number of ANFIS controllers
by incorporating a single controller whose main parameters shall be optimized
by latest optimization techniques, and the results reveal that the proposed strategy

is effective in managing the motor’s speed.

Keywords: Artificial bee colony algorithm; ANFIS; BLDC motor; PI controller;
sensorless control

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