Robust Adaptive Control of Medium-low Speed Maglev Based on Magnetic Nonlinearity
Author:
Affiliation:

Institute of Rail Transit,Tongji University, Shanghai 201804, China

Clc Number:

TP273

  • Article
  • | |
  • Metrics
  • |
  • Reference [23]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    In order to ensure the suspension stability of maglev trains, we investigate the suspension control problem of medium-low speed maglev vehicles under the disturbances of nonlinear magnetic fields and track irregularity in this paper. Firstly, the dynamic and static magnetic field characteristics are analyzed based on the finite element method, and a suspension force model considering magnetic saturation and eddy current effects is established. A mathematical model of a single suspension unit is built on the basis of the suspension force model. Then, a robust adaptive control method is proposed, which flexibly adjusts the control parameters through the adaptive law in the framework of generalized PI control. The Lyapunov method is used to prove that all signals in the closed-loop system are ultimately uniformly bounded. Finally, simulations under various operating conditions are conducted on the whole vehicle dynamics model to verify the effectiveness of the proposed control method. It is shown that air gap tracking errors under the robust adaptive control are both reduced by over 70% under sine and random disturbances, and compared with the traditional PID control, the maximum differences of air gap tracking errors between the front and rear suspension points of the same suspension module decrease from 1.571 8 mm and 1.227 8 mm to 0.195 2 mm and 0.396 2 mm respectively under the condition of vertical curves.

    Reference
    [1] SHU G, MEISINGER R. State estimation and simulation of the magnetic levitation system of a high-speed maglev train[C]//Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology. Piscataway: IEEE, 2011. DOI:10.1109/EMEIT.2011.6023250.
    [2] LIU S, AN B, LIU S, et al. Characteristic research of electromagnetic force for mixing suspension electromagnet used in low-speed maglev train[J]. IET Electric Power Applications, 2015, 9(3): 223.
    [3] NI F, MU S, KANG J, et al. Robust controller design for maglev suspension systems based on improved suspension force model[J]. IEEE Transactions on Transportation Electrification, 2021, 7(3): 1765.
    [4] SCHMID P, EBERHARD P, DIGNATH F. Nonlinear model predictive control for a maglev vehicle regarding magnetic saturation and guideway irregularities[J]. IFAC-PapersOnLine, 2019, 52(15): 145.
    [5] YANG Q, CHI Z, WANG L. Influence and suppression method of the eddy current effect on the suspension system of the EMS maglev train[J]. Machines, 2022, 10(6): 476.
    [6] LINDLAU J D, KNOSPE C R. Feedback linearization of an active magnetic bearing with voltage control[J]. IEEE Transactions on Control Systems Technology, 2002, 10(1): 21.
    [7] BELMONTE L M, SEGURA E, FERNáNDEZ-CABALLERO A, et al. Generalised proportional integral control for magnetic levitation systems using a tangent linearisation approach[J]. Mathematics, 2021, 9(12): 1424.
    [8] 陈琛, 徐俊起, 林国斌, 等. 具有径向基网络加速度反馈的磁浮列车悬浮系统滑模控制[J]. 同济大学学报(自然科学版), 2021, 49(12):1642.CHEN Chen,XU Junqi,LIN Guobin,et al. Sliding mode control of maglev suspension system with radial basis function network acceleration feedback[J]. Journal of Tongji University (Natural Science), 2021, 49(12): 1642.
    [9] SUN Y, XU J, QIANG H, et al. Adaptive sliding mode control of maglev system based on RBF neural network minimum parameter learning method[J]. Measurement, 2019, 141: 217.
    [10] SUN Y, XU J, QIANG H, et al. Adaptive neural-fuzzy robust position control scheme for maglev train systems with experimental verification[J]. IEEE Transactions on Industrial Electronics, 2019, 66(11): 8589.
    [11] SUN Y, XU J, WU H, et al. Deep learning based semi-supervised control for vertical security of maglev vehicle with guaranteed bounded airgap[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22(7): 4431.
    [12] WANG J, RONG J, YANG J. Adaptive fixed-time position precision control for magnetic levitation systems[J]. IEEE Transactions on Automation Science and Engineering, 2023, 20(1): 458.
    [13] 孙友刚, 李万莉, 林国斌, 等. 低速磁浮列车悬浮系统动力学建模及非线性控制[J]. 同济大学学报(自然科学版), 2017, 45(5): 741.SUN Yougang,LI Wanli,LIN Guobin,et al. Dynamic modeling and nonlinear control of suspension system of low-speed maglev train [J]. Journal of Tongji University (Natural Science), 2017, 45(5): 741.
    [14] 贺光. EMS型中速磁浮列车动力学建模与导向能力研究[D].长沙:国防科学技术大学,2016.HE Guang. Research on dynamics modeling and guidance capability of EMS medium speed maglev train[D].Changsha: National University of Defense Technology,2016.
    [15] DAI Y H. A perfect example for the BFGS method[J]. Mathematical Programming, 2013, 138(1): 501.
    [16] 杨志华. 中低速磁浮列车悬浮系统仿真研究[D].成都:西南交通大学,2014.YANG Zhihua. Simulation study on the suspension system of medium and low speed maglev trains[D]. Chengdu: Southwest Jiaotong University,2014.
    [17] 郑丽莉. 钢轨涡流对EMS型低速磁浮列车悬浮力影响的研究[D].长沙:国防科学技术大学,2010.ZHENG Lili. Research on the influence of rail eddy current on the suspension force of EMS low speed maglev train [D].Changsha: National University of Defense Technology,2010.
    [18] TANG X, TAO G, JOSHI S M. Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application[J]. Automatica, 2007, 43(11): 1869.
    [19] CAI W, LIAO X H, SONG Y D. Indirect robust adaptive fault-tolerant control for attitude tracking of spacecraft[J]. Journal of Guidance, Control, and Dynamics, 2008, 31(5): 1456.
    [20] SONG Y D, CHEN H N, LI D Y. Virtual-point-based fault-tolerant lateral and longitudinal control of 4W-steering vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4): 1343.
    [21] SONG Y, WANG Y, WEN C. Adaptive fault-tolerant PI tracking control with guaranteed transient and steady-state performance[J]. IEEE Transactions on Automatic Control, 2017, 62(1): 481.
    [22] SONG Q, SONG Y D. Generalized PI control design for a class of unknown nonaffine systems with sensor and actuator faults[J]. Systems & Control Letters, 2014, 64: 86.
    [23] DING J, YANG X, LONG Z. Structure and control design of levitation electromagnet for electromagnetic suspension medium-speed maglev train[J]. Journal of Vibration and Control, 2019, 25(6): 1179.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

ZHANG Jimin, WANG Hangsheng, REN Qiao. Robust Adaptive Control of Medium-low Speed Maglev Based on Magnetic Nonlinearity[J].同济大学学报(自然科学版),2024,52(11):1776~1785

Copy
Share
Article Metrics
  • Abstract:65
  • PDF: 147
  • HTML: 528
  • Cited by: 0
History
  • Received:December 18,2022
  • Online: December 03,2024
Article QR Code