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A back-stepping neural network control scheme for PM synchronous motors
Conference proceeding

A back-stepping neural network control scheme for PM synchronous motors

J. Wang, K.M. Tsang, N.C. Cheung and Ngai Man Cheung
PEDS 2003 : the 5th International Conference on Power Electronics and Drive Systems : proceedings : 17-20 November 2003, Novotel Apollo Hotel, Singapore, Vol.1, pp.728-732 Vol.1
2003

Abstract

Backstepping Control systems Friction Magnetic flux Neural networks Robots Robustness Synchronous motors Torque Uncertainty
Focusing on the seriously nonlinear problem and unknown or uncertain parameters, a backstepping control method based on neural networks is proposed to realize the multi-object position control of PM synchronous motors. Neural networks in the scheme are used to solve the contradiction between backstepping control and unmatched conditions of systems. A special weight online tuning method is proposed in this paper, and an off-line training phase is not required. The method does not require the system parameters to be exactly known, and the system is robust. The simulation results show that, the proposed method is effective.

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