Magnetic Levitation – Modelling, Identification and Open Loop Verification

Authors

  • Daniel Honc University of Pardubice Pardubice
  • Eleonora Riva Sanseverino University of Palermo Palermo

DOI:

https://doi.org/10.14311/TEE.2019.1.013

Abstract

The paper describes a procedure using the first principle modelling and experimental identification of the Magnetic Levitation Model CE 152. It is a modified version of the paper [1]. The difference is that the identification and verification is done in open loop and constraints logic is added in the current paper. The author optimized and simplified dynamic model to a minimum to what is needed to characterize given system for the simulation and control design purposes. Only few open-loop experiments are needed to estimate the unknown parameters. Model quality is verified in open loop where the real and simulated data are compared. The model can serve as a simulation model for some standard control algorithms or as a process model for advanced control method design.

Author Biographies

Daniel Honc, University of Pardubice Pardubice

Department of Process Control

Eleonora Riva Sanseverino, University of Palermo Palermo

Energia, Ingegneria dell'Informazione e Modelli Matematici

References

D. Honc, “Modelling and identification of magnetic levitation model CE 152/revised,” Advances in Intelligent Systems and Computing, p. 35-43, 2019.

doi: 10.1007/978-3-319-91192-2_4

CE 152 Magnetic Levitation Model, available at: https://www.humusoft.cz/models/ce152/, [Accessed: 14. Feb 2019]

Humusoft: CE 152 Magnetic levitation model – educational manual. Prague: Humusoft s.r.o., 2002.

T. Bächle, S. Hentzelt and K. Graichen, “Nonlinear model predictive control of a magnetic levitation system,” Control Eng. Pract., 21(9):1178-1187, 2013.

doi: 10.1016/j.conengprac.2013.04.009

P. Doležel, P. Rozsíval, M. Mariška and L. Havlíček, “PID controller design for nonlinear oscillative plants using piecewise linear neural network,” In: Proceedings of the 19th International Conference on Process Control, PC 2013; p. 19-24, 2013.

doi: 10.1109/PC.2013.6581376

F. Gazdoš, P. Dostál and J. Marholt, “Robust control of unstable systems: Algebraic approach using sensitivity functions,” Int. J. of Math. Models and Methods in Appl. Sci., 5(7):1189-1196, 2011.

F. Gazdoš, P. Dostál, R. Pelikán and V. Bobál, “Polynomial approach to control system design for a magnetic levitation system,” In: 2007 European Control Conference, ECC 2007; p. 4561-4567, 2007.

doi: 10.23919/ECC.2007.7068308

M. Hypiusová and A. Kozáková, “Robust PID controller design for the magnetic levitation system: Frequency domain approach,” In: Proceedings of the 21st International Conference on Process Control, PC 2017; p. 274-279, 2017.

doi: 10.1109/PC.2017.7976226

P. Chalupa, J. Novák and M. Malý, “Modelling and model predictive control of magnetic levitation laboratory plant,” In: Proceedings - 31st European Conference on Modelling and Simulation, ECMS 2017; p. 367-373, 2017.

doi: 10.7148/2017-0367

Y. Qin, H. Peng and W. Ruan, “Modeling and predictive control of magnetic levitation ball system based on RBF-ARX model with linear functional weights,” Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology); 47(8):2676-2684, 2016.

L. Rušar, A. Krhovják and V. Bobál, “Predictive control of the magnetic levitation model,” In: Proceedings of the 21st International Conference on Process Control, PC 2017; p. 345-350, 2017.

G. Stettinger, M. Benedikt, M. Horn, J. Zehetner and C. Giebenhain, “Control of a magnetic levitation system with communication imperfections: A model-based coupling approach,” Control Eng. Pract.; 58:161-170, 2017.

doi: 10.1016/j.conengprac.2016.10.009

X. Du and Y. Zhang, “An improved method of mathematical model on current controlled magnetic levitation ball system,” Applied Mechanics and Materials. 128-129:70-73, 2012.

R.K.H. Galvão, T. Yoneyama, F.M.U. De Araújo and R.G. Machado, “A simple technique for identifying a linearized model for a didactic magnetic levitation system,” IEEE Trans. On Educ.; 46(1):22-25, 2003.

doi: 10.1109/TE.2002.804403

T.M. Guess and D.G. Alciatore, “Model development and control implementation for a magnetic levitation apparatus,” In: ASME Database Symposium; p. 993-999, 1995.

P. Chalupa, M. Malý and J. Novák, “Nonlinear simulink model of magnetic levitation laboratory plant,” In: Proceedings - 30th European Conference on Modelling and Simulation, ECMS 2016; p. 293-299, 2016.

doi: 10.7148/2016-0293

D. Jiang, J. Yang, L., Ma, L. and D. Jiang, “Model building and simulating for hybrid magnetic levitation ball system,” In: 2010 International Conference on Mechanic Automation and Control Engineering, MACE2010; p. 6105-6110, 2010.

doi: 10.1109/MACE.2010.5536548

R.B. Owen and M. Maggiore, “Implementation and model verification of a magnetic levitation system,” In: Proceedings of the American Control Conference; p. 1142-1147, 2005.

doi: 10.1109/ACC.2005.1470115

A. Pilat, “Modelling, investigation, simulation, and PID current control of Active Magnetic Levitation FEM model,” In: 18th International Conference on Methods and Models in Automation and Robotics, MMAR 2013; p. 299-304, 2013.

doi: 10.1109/MMAR.2013.6669923

R.C. Sankar and M. Chidambaram, “Subspace identification of unstable transfer function model for a magnetic levitation system,” In: IFAC Proceedings Volumes (IFAC-PapersOnline); p. 394-399, 2014.

P. Šuster and A. Jadlovská, “Modeling and control design of magnetic levitation system,” In: IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings; p. 295-299, 2012.

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Published

2020-03-30

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