WNN Optimizing PID Controller for BLDC Control System

Abstract:

Brushless DC motors (BLDC) are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper presents the PID control for BLDC Motor, because good control effect cannot be acquired by using the traditional PID control in the non-linear variable time servomechanism and it is difficult to tune the parameters and get satisfied control characteristics, some intelligent techniques should be taken. Wavelet Neural Network (WNN) was constrictive and fluctuant of wavelet transform and has self-study, self adjustment and nonlinear mapping functions of neural networks, So, a wavelet neural network self-tuning proportional-integral-derivative (PID) controller was proposed. The structure of WNN and PID tuning with WNN was presented and the equivalent circuit of BLDC and its mathematical models was analyzed, the simulation was taken with new method, the efficiency and advantages of this control strategy was successfully demonstrated which can applied into BLDC control system.

• Periodical: Applied Mechanics and Materials (Volumes 278-280)
• Pages: 1529-1532
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.278-280.1529
• Online since: January 2013
• Authors: Hong Pei Han, Wu Wang
• Keywords: Brushless Dc Motor (BLDCM), PID Parameter Tuning, Simulation, Tuning, Wavelet Neural Network (WNN)

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