The Brushless DC motor control system Based on neural network fuzzy PID control of power electronics technology

Abstract

In order to improve The Brushless DC motor control system Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights development of power electronics technology emergence, The brushless director current (DC) motor is a new type of mechatronic motor that has been developed rapidly with the development of power electronics technology, The performance of the brushless DC motor control system, this paper starts with the brushless DC motor to improve the motor structure or use new materials. This paper uses the neural network fuzzy PID control method to carry out the study of the brushless DC motor control system, and chooses the correct control model and control target to solve the influence of the commutation process on the system. Moreover, this paper analyzes and designs the application of model prediction in BLDCM current loop control, and uses this control system to build a simulation model of brushless DC motor control system in MATLAB. The simulation results show that the brushless DC motor control system based on neural network fuzzy PID control can effectively improve the control effect.