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Hybrid Intelligent Control for Speed Sensorless of SPMSM Drive  

Lee Jung-Chul (순천대 공대 정보통신공학부)
Lee Hong-Gyun (순천대 공대 정보통신공학부)
Chung Dong-Hwa (순천대 공대 정보통신공학부)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.53, no.10, 2004 , pp. 690-696 More about this Journal
Abstract
This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.
Keywords
SPMSM Drive; Hybrid Intelligent Control; NNF; ANN; BPA; Speed Estimation;
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