System Identification and Reengineering Controllers for a Magnetic Bearing System
Shi, Juan and Revell, J (2002) System Identification and Reengineering Controllers for a Magnetic Bearing System. In: 2002 IEEE Region 10 International Conference on Computers, Communications, Control and Power Engineering : IEEE TENCOM'02 : October 28-31, 2002, Beijing, China. Yuan, Baozong and Tang, Xiaofang, eds. IEEE, Piscataway, New Jersey, pp. 1591-1594.
Abstract
In this paper, a model of an MBC 500 magnetic bearing system is identified using data collected in the frequency domain. The difficulties encountered in system identification using the MATLAB μ-Analysis and Synthesis toolbox are addressed. Since there are two resonant modes that threaten the stability of the system, two resonant frequencies have been correctly identified and then notched out by using two notch filters. Lead compensators have been designed to stabilise the four axial channels of the magnetic bearing system. The problem with attempting to design a lead compensator with too large a phase margin is also addressed. Finally, the designed notch filters and lead compensators are implemented in real-time.
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Item type | Book Section |
URI | https://vuir.vu.edu.au/id/eprint/25382 |
DOI | 10.1109/TENCON.2002.1182635 |
Official URL | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn... |
ISBN | 0780374908 7900091556 |
Subjects | Historical > FOR Classification > 0906 Electrical and Electronic Engineering Current > Division/Research > Other |
Keywords | closed loop systems, compensation, control system synthesis, frequency estimation, frequency-domain analysis, magnetic bearings, notch filters, real-time systems, MATLAB, MBC 500, axial channel stabilisation, frequency domain data, lead compensators, phase margin, re-engineering controllers, real-time implementation, resonant frequencies, resonant modes, system identification, system stability, control system synthesis, control systems, filters, magnetic levitation, magnetic resonance, magnetic separation, mathematical models, system identification |
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