Neural Network-based Sliding Mode Control for Permanent Magnet Synchronous Motor

2015 ◽  
Vol 9 (1) ◽  
pp. 314-320
Author(s):  
Kaiqi Huang ◽  
Shilin Zuo
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Permanent Magnet ◽  
Sliding Mode ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Mode Control

Terminal sliding mode control of permanent magnet synchronous motor based on the reaching law

2019 ◽  
Vol 234 (7) ◽  
pp. 849-859
Author(s):  
Peikun Zhu ◽  
Yong Chen ◽  
Meng Li
Keyword(s):  
Sliding Mode Control ◽  
Permanent Magnet ◽  
Parameter Uncertainty ◽  
Control Algorithm ◽  
Sliding Mode ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Terminal Sliding Mode ◽  
Reaching Law ◽  
Mode Control

Aiming at the parameter uncertainty and load torque disturbance of permanent magnet synchronous motor system, a terminal sliding mode control algorithm for permanent magnet synchronous motor based on the reaching law is proposed. First, a sliding mode control algorithm for sliding mode reaching law is proposed, which can dynamically adapt to the changes in system state. Second, a sliding mode disturbance observer is designed to estimate the lumped disturbance in real time and to compensate the controller for disturbance. On this basis, an online identification method based on disturbance observer for viscous friction coefficient and moment of inertia is used to reduce the influence of parameter uncertainty on the control system. Simulation and experimental results show the effectiveness of the method.

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