Levitation mechanism modelling for maglev transportation system

Abstract

A novel maglev transportation system was proposed for large travel range ultra precision motion. The system consists of a levitation subsystem and a propulsion subsystem. During the propulsion subsystem driving the moving platform along the guideway, the levitation subsystem uses six pairs of electromagnets to steadily suspend the moving platform over the guideway. The model of the levitation system, which is a typical nonlinear multi-input multi-output coupling system and has many inner nonlinear coupling characteristics, was deduced. For testifying the model, the levitation mechanism was firstly controlled by proportional-integral-differential (PID) control, and then a lot of input-output data were collected for model parameter identification. The least-square parameter identification method was used. The identification results prove that the model is feasible and suitable for the real system.

Keywords

maglev transportation system / levitation mechanism / modeling / parameters identification

References

[1] JingM.-q., LiuH., LianJ.-x., YuLie.. Two-dimensional high precision positioning maglev stage [J]. Journal of Xi’an Jiao Tong University, 2008, 42(11): 1377-1381

[2] KaloustJ., HamC., SiehlingJ., JongekrygE., HanQ.. Nonlinear robust control design for levitation and propulsion of a maglev system [J]. IEE Proceedings—Control Theory Applications, 2004, 151(4): 460-464

[3] WaiR. J., LeeJ. D.. Adaptive fuzzy-neural-network control for maglev transportation system [J]. IEEE Trans on Neural Networks, 2008, 19(1): 54-70

[4] KimW. J., TrumperD. L., LangJ. H.. Modeling and vector control of planar magnetic levitator [J]. IEEE Trans on Ind Applicat, 1998, 34(6): 1254-1262

[5] KuoS. K., ShanX.-m., MenqC. H.. Large travel ultra precision x-y-θ motion control of a magnetic-suspension stage [J]. ASME Trans on Mechatronics, 2003, 8(3): 334-341

[6] ShanX.-m., KuoS. K., ZhangJ.-h., MenqC. H.. Ultra precision motion control of a multiple degrees of freedom magnetic suspension stage [J]. ASME Trans on Mechatronics, 2002, 7(1): 67-78

[7] SinhaP. K., PechevA. N.. Model reference adaptive control of a maglev system with stable maximum descent criterion [J]. Automatica, 1999, 35(8): 1457-1465

[8] LiQ.-m., GaoD., DengH., OuyangHua.. Modal analysis of a high-precision magnetic suspension stage [C]. Proceedings of the 7th World Congress on Intelligent and Automation, 2008, Chongqing, IEEE: 6044-6048

[9] ZhengX.-j., WuJ.-j., ZhouY.-he.. Numerical analysis on dynamic control of five-degree-of-freedom maglev vehicle moving on flexible guideways [J]. Journal of Sound and Vibration, 2000, 235(1): 43-61

[10] LiQ.-m., WanL., ZhuL., XuZhen.. Decoupling control for a magnetic suspension stage [C]. IEEE International Conference on Control and Automation, 2007, Guangzhou, IEEE: 323-328

[11] BoeijJ. D., SteinbuchM., GutierrezH. M.. Mathematical model of the 5-DOF sled dynamics of an electrodynamic maglev system with a passive sled [J]. IEEE Transactions on Magnetics, 2005, 41(1): 460-465

[12] LiH.-x., DengHua.. An approximate internal model-based neural control for unknown nonlinear discrete processes [J]. IEEE Transactions on Neural Networks, 2006, 17(3): 659-670

[13] DingF., ChenT.-wen.. Performance bounds of forgetting factor least-squares algorithms for time-varying systems with finite measurement data [J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2005, 52(3): 555-566

[14] LjungL.System identification: Theory for the user [M], 20022nd ed.Beijing, Tsinghua University Press: 10-260

[15] PaleologuC., BenestyJ., CiochinaS.. A robust variable forgetting factor recursive least-squares algorithm for system identification [J]. IEEE Signal Processing Letters, 2008, 15: 597-600