AI based Vector Control Method for BLDC Motor with Multi Switch Three-Phase Topology

Abstract

Brushless direct current (BLDC) Motors are extensively used because of their characteristics. Such characteristics are high dynamic response and high-power density.  BLDCM control system is a nonlinear, multi-variable, strong-coupling system. In this paper it is proposed that a neural network controller is used for the five level switch of the BLDC motor to enhance the power factor and reduce the current distortions with respect to its rise time, startup torque. This method is also done in comparison with the PID controllers. The working principle of the BLDC is with the help of five-switch control scheme can be implemented here. The different values of load were used to consider the total operation of the BLDC motor is to be controlled. After the completion of the training and testing of the neural network, it might be maintain the constant load values and its variables. To calculate the duty ratio of the DC-DC converter, it will be adjusted to regulate the speed of the BLDC motor. However the DC link of the five switching inverter is used here for the boosting of the voltage.  The effectiveness of the proposed control technique can be realized with help of the speed sensor. Various tests have been conducted in the simulation the proposed technology is the robust technology and it is proven that very effective and suitable control technique.