Designing of Neuro-Fuzzy Controllers for Brushless DC Motor Drives Operating with Multiswitch Three-Phase Topology

Abstract

Brushless DC motors are simple in construction, high efficiency, less noise, and high reliability, which are not replaceable motors in specific applications compared to other motor drives. It has a facility for its multivariable system, nonlinear control process, and powerful coupling system. This paper proposes to design the neuro-fuzzy controllers for its multiple converters switching to improve the power factor and minimize the BLDC motor switching losses. Compared with conventional controllers, this controller will develop the power factor and optimize the current ripples concerning time and torque. The working model of the BLDC motor may be presented here. A nonlinear load will be applied to the BLDC motor to determine the speed, current, and torque. The multiple switches designed with the proposed controllers are connected with the converter’s DC link to boost the voltage. The fuzzy logic controller is implanted to adjust the speed of the neural network and is also designed for the analysis of the stability of the system. The proposed controllers compare the rate at different speeds, torque, currents, and rotor angle positions. Finally, the proposed controller for multiple converter switches performs better than the conventional controllers.