DocumentCode :
1624809
Title :
Self-Sensing Three-Pole Magnetic Bearing Using a Kalman Filter
Author :
Matsuda, Koichi ; Kijimoto, Shinya ; Kanemitsu, Yoichi
Author_Institution :
Dept. of Intelligent Machinery & Syst., Kyushu Univ., Fukuoka
fYear :
2006
Firstpage :
1590
Lastpage :
1594
Abstract :
Self-sensing active magnetic bearing is designed by a new approach. The approach aims to solve the observer bias problem by introducing a Kalman filter. In order to verify the validity of the approach, a Kalman filter is designed for a three-pole homopolar magnetic bearing and used to estimate the radial displacement and velocity of the rotor. The electric current is driven by a linear power-amplifier circuit to flow through the coils, and the coil terminal voltage is passed through an analog first-order low-pass filter with a cut-off frequency of 100 Hz. The designed Kalman filter uses the filtered coil-voltage and the controller inputs as an input for calculating the estimate. The unobservable bias is estimated as an unknown state, and the Kalman-filter estimates are numerically simulated by the measured input/output data. The results show that the bias is successfully estimated to overlap the estimated displacement to its measurement
Keywords :
Kalman filters; low-pass filters; magnetic bearings; power amplifiers; 100 Hz; Kalman filter; analog first-order low-pass filter; linear power-amplifier circuit; radial displacement estimation; rotor velocity estimation; self-sensing active magnetic bearing; three-pole homopolar magnetic bearing; unobservable bias estimation; Circuits; Coils; Current; Cutoff frequency; Frequency estimation; Low pass filters; Magnetic levitation; Magnetic separation; Nonlinear filters; State estimation; Kalman Filter; Magnetic Bearing; Self-Sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
Type :
conf
DOI :
10.1109/SICE.2006.315513
Filename :
4109221
Link To Document :
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