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Proceedings Paper

Control of a magnetic flywheel by a fuzzy neural network algorithm
Author(s): J.-W. Kim; D.-J. Xuan; Y.-B. Kim
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Paper Abstract

In this paper a magnetic flywheel system is studied with a magnetic bearing, which is able to support the shaft without mechanical contacts, and it is also able to control the rotational vibration. Magnetic flywheel system is composed of position sensors, a digital controller, actuating amplifiers, electromagnets and a flywheel. This work applies the fuzzy neural network (FNN) algorithm to control the vibration of a magnetic flywheel system. It proposes the design skill of an optimal controller when the system has the uncertainty, i.e. it has a difficulty in extracting the exact mathematical expressions. Two controllers are designed for the FNN in order to reduce the rotor vibration effectively. Unbalance response, which is a serious problem in rotating machineries, is improved by using a magnetic bearing with a FNN algorithm.

Paper Details

Date Published: 2 May 2006
PDF: 6 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 604229 (2 May 2006); doi: 10.1117/12.664650
Show Author Affiliations
J.-W. Kim, Chonnam National Univ. (South Korea)
D.-J. Xuan, Chonnam National Univ. (South Korea)
Y.-B. Kim, Chonnam National Univ. (South Korea)

Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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