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CLC number: TP13
On-line Access: 2019-01-30
Received: 2018-09-28
Revision Accepted: 2018-12-25
Crosschecked: 2019-01-08
Cited: 0
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On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws
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Xujun Lyu, Long Di, Zongli Lin. On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 120-130.
@article{title="On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws",
author="Xujun Lyu, Long Di, Zongli Lin",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="20",
number="1",
pages="120-130",
year="2019",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800606"
}
%0 Journal Article
%T On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws
%A Xujun Lyu
%A Long Di
%A Zongli Lin
%J Frontiers of Information Technology & Electronic Engineering
%V 20
%N 1
%P 120-130
%@ 2095-9184
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800606
TY - JOUR
T1 - On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws
A1 - Xujun Lyu
A1 - Long Di
A1 - Zongli Lin
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 1
SP - 120
EP - 130
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1800606
Abstract: A characteristic model based all-coefficient adaptive control law was recently implemented on an experimental test rig for high-speed energy storage flywheels suspended on magnetic bearings. Such a control law is an intelligent control law, as its design does not rely on a pre-established mathematical model of a plant but identifies its characteristic model while the plant is being controlled. Extensive numerical simulations and experimental results indicated that this intelligent control law outperforms a $mu$-synthesis control law, originally designed when the experimental platform was built in terms of their ability to suppress vibration on the high-speed test rig. We further establish, through an extensive simulation, that this intelligent control law possesses considerable robustness with respect to plant uncertainties, external disturbances, and time delay.
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