A Novel Terminal Sliding Mode Control Based on RBF Neural Network for the Permanent Magnet Synchronous Motor

Author(s):  
Yang Ge ◽  
Lihui Yang ◽  
Xikui Ma
2013 ◽  
Vol 365-366 ◽  
pp. 887-896
Author(s):  
Liang Qi ◽  
Yan Zhu Yang ◽  
Xu Bai ◽  
Hong Bo Shi ◽  
Wei Liang Liu

In this paper, the main factors which influence the current control performance of the Permanent Magnet Synchronous Motor are studied and analyzed. A method, which combines the fast terminal sliding mode control and the current feed forward control methods, is proposed to solve the problems of the cross-coupling of d-q current in field oriented control. Meanwhile, an adaptive control law is designed for the system uncertainties of system parameters perturbation and external disturbances and so on. The convergence of the proposed method is proved by Lyapunov theory. The proposed control method is testified by computer simulation and improves the robustness of the Permanent Magnet Synchronous Motor control system.


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