An intelligent feedback control mechanism for brushless DC motors

This paper presents a new approach to control a Brushless Direct Current (BLDC) motor using Artificial Neural Networks (ANNs). An intelligent Proportional-Integral-Derivative (PID) feedback controller was developed to apply to the BLDC motor controller. The proposed motor model is created in MATLAB/Simulink, and the ANN controller is trained with collected data from a PID controller, to supply the required voltage to the motor phases. Rotor position collected data from an incremental encoder is used as the main feedback signal. Simulation data are collected for both the cascaded PID controller and the trained ANN, and then their relative performances are analyzed. In addition, this ANN based structure can be applied in different controllers.