Abstract
The primary aim of this paper is to control the speed of brushless DC motor using Artificial Neural Network (ANN) controller and PID controller. Detailed analysis is performed based on the simulation results of both the methods. A neural control based speed control system of brushless DC motor is designed by analyzing the mathematical model of BLDC motor. Plant model identification is done in Simulink software of MATLAB to identify the ANN block of BLDC motor drive system. Reference control model is designed to give the ideal values of control parameters when the control system responds to the command signal. The performance results of PID controller and ANN controller are compared with reference model output of BLDC motor drive system in MATLAB Simulink environment. Comparative study concludes that ANN based speed control method eliminates the overshoot, reduces the settling time of the system response. It is observed that the ANN based simulation results are closer to the ideal reference control model response than PID based.
Published Version
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