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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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Published in: | IEEE access 2024-01, Vol.12, p.1-1 |
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creator | Lu, Yufang Huang, Jiehui Jiang, Zhijun Tang, Tao Tang, Haihua Shi, Lei |
description | 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. |
doi_str_mv | 10.1109/ACCESS.2024.3393029 |
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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 |
title | PID Adaptive Feedback Motor System Based on Neural Network |
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