Active Control of Vertical Vibration for Maglev Train Based on Artificial Intelligence Load Estimation System

被引：0

作者：

Chen C. ^{[1
,2
,3
]}

Xu J. ^{[2
]}

Ni F. ^{[2
]}

Lin G. ^{[2
]}

Wu H. ^{[4
]}

机构：

[1] Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai

[2] Maglev Transportation Engineering R&D Center, Tongji University, Shanghai

[3] College of Transportation, Tongji University, Shanghai

[4] Key Laboratory for Mechanics in Fluid Solid Coupling Systems, Institute of Mechanics of Chinese Academy of Sciences, Beijing

来源：

Ni, Fei (fei.ni@tongji.edu.cn) | 1600年 / Science Press卷 / 48期

关键词：

Active control; Artificial neural network; Load estimation; Maglev train; Nonlinear model of levitation system;

D O I：

10.11908/j.issn.0253-374x.20058

中图分类号：

学科分类号：

摘要：

An active control strategy of maglev train suspension system based on artificial intelligence load estimation system is proposed in this paper. Firstly, the mathematical model of single-point levitation is given, and the open-loop instability is proven by the Routh-Herwitz criterion. Secondly, considering the load characteristics and the real-time suspension changes, a multi-layer artificial neural network is constructed to control the output of the control variables for the suspension system. Thirdly, the non-dominated sorting genetic algorithm (NSGA) is used to optimize the system parameters. The results show that the proposed control method has better robustness and can still keep relatively small error under large load disturbance. © 2020, Editorial Department of Journal of Tongji University. All right reserved.

引用

页码：1344 / 1352

页数：8

共 19 条

[1]

LEE H W, KIM K C, LEE J., Review of maglev train technologies, IEEE Transactions on Magnetics, 42, 7, (2006)

[2]

SUN Y G, LI W L, QIANG H Y, Et al., An experimental study on the vibration of the low-speed maglev train moving on the guideway with sag vertical curves, International Journal of Control and Automation, 9, 4, (2016)

[3]

XU Fei, LUO Shihui, DENG Zigang, Study on key technologies and whole speed range application of maglev rail transport, Journal of China Railway Society, 3, (2019)

[4]

LONG Zhiqiang, HAO Aming, CHANG Wensen, Suspension controller design of maglev train considering the rail track periodical irregularity, Journal of National University of Defense Technology, 25, 2, (2003)

[5]

LINDLAU J D, KNOSPE C R., Feedback linearization of an active magnetic bearing with voltage control, IEEE Transactions on Control Systems Technology, 10, 1, (2002)

[6]

SONG Wenrong, YU Guofei, WANG Yanfeng, Et al., PID control of micro feed mechanism based on magnetic levitation technology, Journal of Harbin Institute of Technology, 36, 1, (2004)

[7]

DAI Liming, QI Bin, ZHOU Haibo, Et al., PID control and experiment for magnetism levitation movement system, Modern Manufacturing Engineering, 6, (2008)

[8]

WANG Hui, ZHONG Xiaobo, SHEN Gang, A new maglev line system design and control strategy, Journal of Tongji University:Natural Science, 41, 7, (2012)

[9]

SUN Y G, QIANG H Y, LIN G B, Et al., Dynamic modeling and control of nonlinear electromagnetic suspension systems, Chemical Engineering Transactions, 46, (2015)

[10]

HE G, LI J, CUI P., Nonlinear control scheme for the levitation module of maglev train, Journal of Dynamic Systems, Measurement & Control, 138, 7, (2016)

← 1 2 →