Study on the sensorless control method of permanent magnet synchronous motor based on self-tuned boundary layer and RBF neural network

Study on the sensorless control method of permanent magnet synchronous motor based on self-tuned boundary layer and RBF neural network

This study develops a proportional-integral-derivative (PID) control framework synthesizing self-tuning boundary layer sliding mode observers with radial basis function (RBF) neural networks. This approach enables adaptive adjustment of the velocity loop PI controller and boundary layer self-tuning...

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Bibliographic Details
Main Authors: Guozhong Yao, Junhong Zhou, Yuhan Xiao, Dewen Jia, Zhengjiang Wang
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
Subjects:
Permanent magnet synchronous motor
Sensorless control
Sliding mode observer
Self-tuning boundary layer
RBF neural network
PID parameter self-tuning
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025018870
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