PID Adaptive Feedback Motor System Based on Neural Network

This paper presents a neural network-based feedback control method for enhancing the control precision and tracking speed of a permanent magnet brushless motor under command control. The proposed method involves real-time adjustment of the PID controller parameters using electromechanical output sig...

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Bibliographic Details
Published in:IEEE access 2024-01, Vol.12, p.1-1
Main Authors: Lu, Yufang, Huang, Jiehui, Jiang, Zhijun, Tang, Tao, Tang, Haihua, Shi, Lei
Format: Article
Language:English
Subjects:
Adaptive control
BP neural network
Brushless motors
Control methods
Control systems
Dynamic loads
Feedback
Feedback control
motor system
Motors
Neural networks
PD control
Permanent magnets
PI control
PID control
PMSM
Proportional integral derivative
Real time
Tracking control
Training
Waveforms
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Summary:This paper presents a neural network-based feedback control method for enhancing the control precision and tracking speed of a permanent magnet brushless motor under command control. The proposed method involves real-time adjustment of the PID controller parameters using electromechanical output signals, enabling adaptive feedback control based on motor output. Experimental results demonstrate that this approach enhances real-time performance and dynamic load response capability, resulting in a current waveform with excellent tracking and low distortion. Overall, this method effectively improves and enhances control effectiveness. Furthermore, the developed control method is successfully applied to the development of tangible products.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3393029