Full Text:   <543>

Summary:  <193>

CLC number: TP273

On-line Access: 2018-02-06

Received: 2017-05-21

Revision Accepted: 2017-07-13

Crosschecked: 2017-12-20

Cited: 0

Clicked: 1484

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.12 P.2035-2045

http://doi.org/10.1631/FITEE.1700324


Model-free adaptive control for three-degree-of-freedom hybrid magnetic bearings


Author(s):  Ye Yuan, Yu-kun Sun, Qian-wen Xiang, Yong-hong Huang, Zhi-ying Zhu

Affiliation(s):  School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China; more

Corresponding email(s):   sykujs421@163.com

Key Words:  Model-free adaptive control, Hybrid magnetic bearings, Nonlinear areas, Faster response, Higher stability


Ye Yuan, Yu-kun Sun, Qian-wen Xiang, Yong-hong Huang, Zhi-ying Zhu. Model-free adaptive control for three-degree-of-freedom hybrid magnetic bearings[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(12): 2035-2045.

@article{title="Model-free adaptive control for three-degree-of-freedom hybrid magnetic bearings",
author="Ye Yuan, Yu-kun Sun, Qian-wen Xiang, Yong-hong Huang, Zhi-ying Zhu",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="12",
pages="2035-2045",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700324"
}

%0 Journal Article
%T Model-free adaptive control for three-degree-of-freedom hybrid magnetic bearings
%A Ye Yuan
%A Yu-kun Sun
%A Qian-wen Xiang
%A Yong-hong Huang
%A Zhi-ying Zhu
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 12
%P 2035-2045
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700324

TY - JOUR
T1 - Model-free adaptive control for three-degree-of-freedom hybrid magnetic bearings
A1 - Ye Yuan
A1 - Yu-kun Sun
A1 - Qian-wen Xiang
A1 - Yong-hong Huang
A1 - Zhi-ying Zhu
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 12
SP - 2035
EP - 2045
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700324


Abstract: 
Mathematical models are disappointing due to uneven distribution of the air gap magnetic field and significant unmodeled dynamics in magnetic bearing systems. The effectiveness of control deteriorates based on an inaccurate mathematical model, creating slow response speed and high jitter. To solve these problems, a model-free adaptive control (MFAC) scheme is proposed for a three-degree-of-freedom hybrid magnetic bearing (3-DoF HMB) control system. The scheme for 3-DoF HMB depends only on the control current and the objective balanced position, and it does not involve any model information. The design process of a parameter estimation algorithm is model-free, based directly on pseudo-partial-derivative (PPD) derived online from the input and output data information. The rotor start-of-suspension position of the HMB is regulated by auxiliary bearings with different inner diameters, and two kinds of operation situations (linear and nonlinear areas) are present to analyze the validity of MFAC in detail. Both simulations and experiments demonstrate that the proposed MFAC scheme handles the 3-DoF HMB control system with start-of-suspension response speed, smaller steady state error, and higher stability.

三自由度混合磁轴承无模型自适应控制系统

概要:由于气隙磁场分布不均以及未建模动态性,数学模型不再适用于磁力轴承系统。基于错误数学模型的系统控制会表现出低响应和高颤动。为解决这一问题,本文提出一种三自由度混合磁轴承无模型自适应控制系统。该控制系统仅与控制电流和轴承的平衡位置有关。其参数估计算法的设计与模型无关,直接基于输入和输出数据的伪偏导数。本文通过不同直径的辅助轴承分析了三自由度混合磁轴承转子悬浮区域,以及通过两种不同的操作系统具体分析无模型自适应控制系统的可行性。模拟和实验结果表明,该三自由度混合磁轴承无模型自适应控制系统具有响应速度快,稳态误差小,和稳定性好等优势。

关键词:模型自适应控制;混合磁轴承;非线性区域;快速响应;高稳定性

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

Reference

[1]Cao, X., Deng, Z.Q., 2010. A full-period generating mode for bearingless switched reluctance generators. IEEE Trans. Appl. Supercond., 20(3):1072-1076.

[2]Casella, F., 2004. Modeling, simulation, control, and optimization of a geothermal power plant. IEEE Trans. Energy Conv., 19(1):170-178.

[3]Chen, L., Hofmann, W., 2012. Speed regulation technique of one bearingless 8/6 switched reluctance motor with simpler single winding structure. IEEE Trans. Ind. Electron., 59(6):2592-2600.

[4]Chen, S.L., Weng, C.C., 2010. Robust control of a voltage-controlled three-pole active magnetic bearing system. IEEE/ASME Trans. Mechatron., 15(3):381-388.

[5]Cimuca, G., Breban, S., Radulescu, M.M., et al., 2010. Design and control strategies of an induction-machine-based flywheel energy storage system associated to a variable-speed wind generator. IEEE Trans. Energy Conv., 25(2): 526-534.

[6]Fang, J.C., Sun, J.J., Liu, H., et al., 2010. A novel 3-DoF axial hybrid magnetic bearing. IEEE Trans. Magn., 46(12): 4034-4045.

[7]Formentin, S., Savaresi, S.M., Del Re, L., 2012. Non-iterative direct data-driven controller tuning for multivariable systems: theory and application. IET Contr. Theory Appl., 6(9):1250-1257.

[8]Han, B.C., Zheng, S.Q., Le, Y., et al., 2013. Modeling and analysis of coupling performance between passive magnetic bearing and hybrid magnetic radial bearing for magnetically suspended flywheel. IEEE Trans. Magn., 49(10):5356-5370.

[9]Hildebrand, R., Lecchini, A., Solari, G., et al., 2005. Asymptotic accuracy of iterative feedback tuning. IEEE Trans. Autom. Contr., 50(8):1182-1185.

[10]Kang, M.S., Lyou, J., Lee, J.K., 2010. Sliding mode control for an active magnetic bearing system subject to base motion. Mechatronics, 20(1):171-178.

[11]Lee, J., Jeong, S., Han, Y.H., et al., 2011. Concept of cold energy storage for superconducting flywheel energy storage system. IEEE Trans. Appl. Supercond., 21(3): 2221-2224.

[12]Mišković, L., Karimi, A., Bonvin, D., et al., 2007. Correlation-based tuning of decoupling multivariable controllers. Automatica, 43(9):1481-1494.

[13]Morrison, C.R., Siebert, M.W., Ho, E.J., 2008. Electromagnetic forces in a hybrid magnetic-bearing switched- reluctance motor. IEEE Trans. Magn., 44(12):4626-4638.

[14]O’Sullivan, D.L., Lewis, A.W., 2011. Generator selection and comparative performance in offshore oscillating water column ocean wave energy converters. IEEE Trans. Energy Conv., 26(2):603-614.

[15]Sala, A., Esparza, A., 2005. Extensions to “virtual reference feedback tuning: a direct method for the design of feedback controllers”. Automatica, 41(8):1473-1476.

[16]Sarkar, S., Ajjarapu, V., 2011. MW resource assessment model for a hybrid energy conversion system with wind and solar resources. IEEE Trans. Sustain. Energy, 2(4):383-391.

[17]Subkhan, M., Komori, M., 2011. New concept for flywheel energy storage system using SMB and PMB. IEEE Trans. Appl. Supercond., 21(3):1485-1488.

[18]Wakitani, S., Yamamoto, T., 2014. Design and application of a data-driven PID controller. Proc. IEEE Conf. on Control Applications, p.1443-1448.

[19]Wang, K., Wang, D., Lin, H.Y., et al., 2014. Analytical modeling of permanent magnet biased axial magnetic bearing with multiple air gaps. IEEE Trans. Magn., 50(11):1-4.

[20]Wei, K.Y., Liu, D.Z., Meng, J., et al., 2010. Design and simulation of a 12-phase flywheel energy storage generator system with linearly dynamic load. IEEE Trans. Appl. Supercond., 20(3):1050-1054.

[21]Xu, J.X., Hou, Z.S., 2009. Notes on data-driven system approaches. Acta Autom. Sin., 35(6):668-675.

[22]Yang, G., Deng, Z.Q., Cao, X., et al., 2008. Optimal winding arrangements of a bearingless switched reluctance motor. IEEE Trans. Power Electron., 23(6):3056-3066.

[23]Yang, Y., Deng, Z.Q., Yang, G., et al., 2010. A control strategy for bearingless switched-reluctance motors. IEEE Trans. Power Electron., 25(11):2807-2819.

[24]Yuan, Y., Sun, Y.K., Huang, Y.H., et al., 2015. Harmony chaotic search optimal design of single winding bearingless switched reluctance flywheel motors. Tran. China Electrotechn. Soc., 30(2):180-188 (in Chinese).

[25]Zhang, C., Tseng, K.J., 2007. A novel flywheel energy storage system with partially-self-bearing flywheel-rotor. IEEE Trans. Energy Conv., 22(2):477-487.

[26]Zhu, Y.M., Hou, Z.S., 2015. Controller dynamic linearisation-based model-free adaptive control framework for a class of non-linear system. IET Contr. Theory Appl., 9(7): 1162-1172.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE