Disturbance Rejection Control Using a Novel Velocity Fusion Estimation Method for Levitation Control Systems

被引:3
作者
Xia, Wentao [1 ]
Long, Zhiqiang [1 ]
Dou, Fengshan [1 ]
机构
[1] Natl Univ Def Technol, Coll Intelligence Sci & Technol, Changsha 410073, Peoples R China
关键词
Disturbance rejection; signal processing; levitation control; PID; differentiator; MAGNETIC SUSPENSION; BALANCE SYSTEM; VIBRATION;
D O I
10.1109/ACCESS.2020.3024665
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Magnetic levitation has been applied to maglev trains and magnetic suspension wind tunnel. However, there are some problems with the existing levitation control. For example, it is difficult to extract smooth velocity signals from the gap sensor with noise. The classical differentiator is susceptible to noise, which makes the levitation system sometimes vibrate. The accuracy and stability of levitation control need to be improved. The velocity fusion estimation method (VFE) is proposed to extract the velocity signal from the gap and acceleration sensor, which is theoretically derived to prove that it reduced the noise of the velocity signal. Then disturbance rejection control(DRC) is proposed that add VFE into classical levitation control. Because of the high-quality velocity signal and accelerometer's fast responsiveness, it makes DRC have many advantages. The advantages of using the proposed control structure are that it improved the control accuracy of the target gap and resisted disturbance effectively. Air-gap fluctuations in levitation systems can be reduced in transient pulse disturbance test, white noise disturbance test, and external force disturbance test when it applies the proposed control method. The effectiveness and advantages of the proposed control method are verified by the simulation and experiments.
引用
收藏
页码:173092 / 173102
页数:11
相关论文
共 36 条
[1]  
Covert E. E., 1973, PROG AEROSPACE SCI, V14, P27
[2]   IMC based PID Control of a Magnetic Levitation System [J].
Duka, Adrian-Vasile ;
Dulau, Mircea ;
Oltean, Stelian-Emilian .
9TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING, INTER-ENG 2015, 2016, 22 :592-599
[3]   Control of magnetic levitation system using recurrent neural network-based adaptive optimal backstepping strategy [J].
Fatemimoghadam, Armita ;
Toshani, Hamid ;
Manthouri, Mohammad .
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2020, 42 (13) :2382-2395
[4]   Effects of the guideway's vibrational characteristics on the dynamics of a Maglev vehicle [J].
Han, H. S. ;
Yim, B. H. ;
Lee, N. J. ;
Hur, Y. C. ;
Kim, S. S. .
VEHICLE SYSTEM DYNAMICS, 2009, 47 (03) :309-324
[5]  
Han H S., 2018, Magnetic Levitation: Maglev Technology and Applications
[6]   From PID to Active Disturbance Rejection Control [J].
Han, Jingqing .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2009, 56 (03) :900-906
[7]   Particle Swarm Optimization-Based Gyro Drift Estimation Method for Inertial Navigation System [J].
He, Hongyang ;
Zhu, Bing ;
Zha, Feng .
IEEE ACCESS, 2019, 7 :55788-55796
[8]   Informative frequency band selection in the presence of non-Gaussian noise - a novel approach based on the conditional variance statistic with application to bearing fault diagnosis [J].
Hebda-Sobkowicz, Justyna ;
Zimroz, Radoslaw ;
Pitera, Marcin ;
Wylomanska, Agnieszka .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 145
[9]   Bridging the gap between sensor noise modeling and sensor characterization [J].
Jerath, Kshitij ;
Brennan, Sean ;
Lagoa, Constantino .
MEASUREMENT, 2018, 116 :350-366
[10]   Compensation of gap sensor for high-speed maglev train with RBF neural network [J].
Jing, Yongzhi ;
Xiao, Jian ;
Zhang, Kunlun .
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2013, 35 (07) :933-939