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Estimation and Control of Speed of Induction Motor using FNN and ANN  

Lee Jung-Chul (School of Information & Communication Engineering. Sunchon National University)
Park Gi-Tae (School of Information & Communication Engineering. Sunchon National University)
Chung Dong-Hwa (School of Information & Communication Engineering. Sunchon National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.42, no.6, 2005 , pp. 77-82 More about this Journal
Abstract
This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. 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 experimental results to verify the effectiveness of the new method.
Keywords
Induction Motor Drive; FNN; ANN; BPA; Speed Control; Speed Estimation;
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