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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

Clicked: 707

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Xujun Lyu

http://orcid.org/0000-0002-2466-2338

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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.1 P.120-130

10.1631/FITEE.1800606


On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws


Author(s):  Xujun Lyu, Long Di, Zongli Lin

Affiliation(s):  College of Engineering, Huazhong Agricultural University, Wuhan 430070, China; more

Corresponding email(s):   lyuxujun@mail.hzau.edu.cn, ld4vv@virginia.edu, zl5y@virginia.edu

Key Words:  Intelligent control, Robustness, Uncertainty, Disturbance rejection, Active magnetic bearings, Energy storage flywheels


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.

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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.

基于特征模型的全系数自适应磁悬浮储能飞轮控制算法鲁棒性研究

摘要:基于特征模型的全系数自适应控制算法最近在一个磁悬浮轴承支承的高速储能飞轮实验平台实现。该控制算法是一个智能控制算法,它的设计不依赖于对象的数学模型,但能在控制过程中在线辨识特征模型。大量数值仿真和实验结果表明,此智能控制算法控制效果比原有μ综合控制算法更好,该μ综合控制算法最初在高速实验台上根据其抑制振动能力设计。大量仿真进一步证实此智能控制算法在考虑模型不确定性、外界扰动以及时滞情况下具有相当强鲁棒性。

关键词:智能控制;鲁棒性;不确定性;抗干扰;主动磁悬浮轴承;储能飞轮

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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