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Self-tuning control of parametrically excited active magnetic bearing system due to harmonic base motion using fuzzy logic
Using active magnetic bearings for vibration control of flexible rotors subject to large base motion is both interesting and challenging. Rotors on ships, airplanes, and space-crafts fall in this category. These applications pose challenge for the active magnetic bearing designer, as the large motio...
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Published in: | Journal of vibration and control 2023-03, Vol.29 (5-6), p.1191-1204 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Using active magnetic bearings for vibration control of flexible rotors subject to large base motion is both interesting and challenging. Rotors on ships, airplanes, and space-crafts fall in this category. These applications pose challenge for the active magnetic bearing designer, as the large motion of base renders the rotor-shaft-AMB system, time varying in nature, and also causes parametric excitation to the rotor system. Apart from stability concerns in such systems, it is difficult to design and choose optimal values of controller parameters because the system is subject to different base motions at different times during operation. In order to address this issue, this work applies fuzzy logic and proposes a simple yet effective selftuning control (STC) to control vibrations of flexible rotors supported by active magnetic bearings, which is subject to excitations due to base motion, in addition to unbalance excitation, usually present in rotors. To this end, first, the controller parameters are optimized considering the levitation performance of active magnetic bearings based on the transient response. Next, the fuzzy logic-based self-tuning algorithm is presented. Detailed comparison of performance between optimal and self-tuning control for different base motion conditions show that the proposed self-tuning controller outperforms the optimal control. |
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ISSN: | 1077-5463 1741-2986 |
DOI: | 10.1177/10775463211059867 |