Volume 20, Issue 7 (July 2020)
Modares Mechanical Engineering 2020, 20(7): 1741-1748 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Dalir M, Bigdeli N. Robust Adaptive Intelligent Controller Design for Magnetic Levitation System with Time Delay, Uncertainty and External Disturbance. Modares Mechanical Engineering 2020; 20 (7) :1741-1748
URL: http://mme.modares.ac.ir/article-15-22006-en.html
URL: http://mme.modares.ac.ir/article-15-22006-en.html
1- Electronic Engineering Department, Engineering Faculty, International Imam Khomeini University, Qazvin, Iran
2- Electronic Engineering Department, Engineering Faculty, International Imam Khomeini University, Qazvin, Iran , n.bigdeli@eng.ikiu.ac.ir
2- Electronic Engineering Department, Engineering Faculty, International Imam Khomeini University, Qazvin, Iran , n.bigdeli@eng.ikiu.ac.ir
Abstract: (2902 Views)
Today, the magnetic levitation system is widely used in various industries. This system is inherently unstable and nonlinear, which is presented by nonlinear equations. On the other hand, the existence of a time delay in these systems also causes system instability or even chaos, which creates additional problems in their control, thus requiring the design of robust and optimal control. In this paper, a robust adaptive intelligent controller based on the backstepping-sliding mode is proposed for the stability and proper tracking of the magnetic levitation system in the presence of time delay, uncertainty, and external disturbances. Due to changes in the equilibrium point, comparative control is used to update the system's momentary information and intelligent controller to estimate uncertainties and disturbances and non-linearity of the system. A robust controller is used to asymptomatic stabilize the Maglev system. The Lyapunov stability theory is used to analyze the stability of the magnetic levitation system with the proposed controller. In the end, in order to demonstrate the performance of the proposed controller, numerical simulations have been used in MATLAB software. The simulation results show that good tracking has been performed and the controller is very good against noise and disturbance.
Article Type: Original Research |
Subject:
Control
Received: 2018/06/16 | Accepted: 2019/12/30 | Published: 2020/07/20
Received: 2018/06/16 | Accepted: 2019/12/30 | Published: 2020/07/20
References
1. Kaplan BZ, Regev D. Dynamic stabilization of tuned-circuit levitators. IEEE Transactions on Magnetics. 1976;12(5):556-559. [Link] [DOI:10.1109/TMAG.1976.1059092]
2. Downer JR. Analysis of a single axis magnetic suspension system [dissertation]. Cambridge: Massachusetts Institute of Technology; 1980. [Link]
3. Dussaux M. The industrial applications of the active magnetic bearing technology. In: Higuchi T, editor. Proceeding of 2nd International Symposium on Magnetic Bearing, July 12-14 1990, Tokyo, Japan. Tokyo: Institute of Industrial Science; 1990. [Link]
4. Limbert DA, Richardson HH, Wormley DN. Controlled dynamic characteristics of ferromagnetic vehicle suspensions providing simultaneous lift and guidance. Journal of Dynamic Systems, Measurement, and Control. 1979;101(3):217-222. [Link] [DOI:10.1115/1.3426428]
5. Torres LHS, Schnitman L, Júnior CAVV, Felippe de Souza JAM. Feedback linearization and model reference adaptive control of a magnetic levitation system. Studies in Informatics and Control. 2012;21(1):67-74. [Link] [DOI:10.24846/v21i1y201208]
6. Morales R, Sira-Ramírez H. Trajectory tracking for the magnetic ball levitation system via exact feedforward linearisation and GPI control. International Journal of Control. 2010;83(6):1155-1166. [Link] [DOI:10.1080/00207171003642196]
7. Slotine JJE, Li W. Applied nonlinear control. New Jersey: Prentice Hall; 1991;199(1). [Link]
8. Zhao F, Loh SC, May JA. Phase-space nonlinear control toolbox: The maglev experience. In: Antsaklis P, Lemmon M, Kohn W, Nerode A, Sastry S, editors. International Hybrid Systems Workshop. 1567th Volume. Heidelberg: Springer; 1997. [Link]
9. Shakir H, Kim WJ. Nanoscale path planning and motion control with maglev positioners. IEEE/ASME Transactions on Mechatronics. 2006;11(5):625-633. [Link] [DOI:10.1109/TMECH.2006.882995]
10. Xiao J, Kulakowski BT. Sliding mode control of active suspension for transit buses based on a novel air-spring model. Proceedings of the 2003 American Control Conference, 4-6 June 2003, Denver, CO, USA. Piscataway: IEEE; 2003. [Link]
11. Cho D, Kato Y, Spilman D. Sliding mode and classical controllers in magnetic levitation systems. IEEE Control Systems Magazine. 1993;13(1):42-48. [Link] [DOI:10.1109/37.184792]
12. Kim YC, Kim KH. Gain scheduled control of magnetic suspension system. Proceedings of 1994 American Control Conference - ACC '94, 29 June-1 July 1994, Baltimore, MD, USA. Piscataway: IEEE; 2002. [Link]
13. Kaloust J, Ham C, Siehling J, Jongekryg E, Han Q. Nonlinear robust control design for levitation and propulsion of a maglev system. IEE Proceedings-Control Theory and Applications. 2004;151(4):460-464. [Link] [DOI:10.1049/ip-cta:20040547]
14. de Queiroz MS, Dawson DM. Nonlinear control of active magnetic bearings: A backstepping approach. IEEE Transactions on Control Systems Technology. 1996;4(5):545-552. [Link] [DOI:10.1109/87.531920]
15. Delavari H, Heydarinejad H. Adaptive fractional order Backstepping sliding mode controller design for a magnetic levitation system. Modares Mechanical Engineering. 2017;17(3):187-195. [Persian] [Link]
16. Shiakolas PS, Van Schenck SR, Piyabongkarn D, Frangeskou I. Magnetic levitation hardware-in-the-loop and MATLAB-based experiments for reinforcement of neural network control concepts. IEEE Transactions on Education. 2004;47(1):33-41. [Link] [DOI:10.1109/TE.2003.817616]
17. Phuah J, Lu J, Yasser M, Yahagi T. Neuro-sliding mode control for magnetic levitation systems. IEEE International Symposium on Circuits and Systems, 23-26 May 2005, Kobe, Japan. Piscataway: IEEE; 2005 [Link]
18. Buckner GD. Intelligent bounds on modeling uncertainty: Applications to sliding mode control. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews). 2002;32(2):113-124. [Link] [DOI:10.1109/TSMCC.2002.801350]
19. Yang J, Sun R, Cui J, Ding X. Application of composite fuzzy-PID algorithm to suspension system of Maglev train. 30th Annual Conference of IEEE Industrial Electronics Society, 2-6 Nov. 2004, Busan, South Korea. Piscataway: IEEE; 2005. [Link]
20. Trumper DL, Olson SM, Subrahmanyan PK. Linearizing control of magnetic suspension systems. IEEE Transactions on Control Systems Technology. 1997;5(4):427-438. [Link] [DOI:10.1109/87.595924]
21. Sun Y, Xu J, Qiang H, Chen C, Lin CG. Adaptive sliding mode control of maglev system based on RBF neural network minimum parameter learning method. Measurement. 2019;141:217-226. [Link] [DOI:10.1016/j.measurement.2019.03.006]
22. Busłowicz M, Nartowicz T. Fractional order controller for a class of inertial plant with delay. Pomiary Automatyka Robotyka. 2009;2(2009):398-405. [Link]
23. Albertos P, García P. Robust control design for long time-delay systems. Journal of Process Control. 2009;19(10):1640-1648. [Link] [DOI:10.1016/j.jprocont.2009.05.006]
24. Sekhar Mishra S, Kumar Mishra S, Kumar Swain S. Coefficient diagram method (CDM) based PID controller design for magnetic levitation system with time delay. IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), 23-25 March 2017, Srivilliputhur, India. Piscataway: IEEE; 2018. [Link] [DOI:10.1109/ITCOSP.2017.8303095]
25. Kumar T, Kumar Mishra S, Kumar Swain S. Design of fractional order controllers satisfying frequency domain specifications for magnetic levitation system with time delay. IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), 23-25 March 2017, Srivilliputhur, India. Piscataway: IEEE; 2018. [Link] [DOI:10.1109/ITCOSP.2017.8303099]
26. Qin Y, Peng H, Ruan W, Wu J, Gao J. A modeling and control approach to magnetic levitation system based on state-dependent ARX model. Journal of Process Control. 2014;24(1):93-112. [Link] [DOI:10.1016/j.jprocont.2013.10.016]
27. Boonsatit N, Pukdeboon C. Adaptive fast terminal sliding mode control of magnetic levitation system. Journal of Control. Automation and Electrical Systems. 2016;27:359-367. [Link] [DOI:10.1007/s40313-016-0246-2]
28. Aliasghary M, Teshnehlab M, Jalilvand A, Aliyari Shoorehdeli M, Nekoui MA. Hybrid control of magnetic levitation system based-on new intelligent sliding mode control. Journal of Applied sciences. 2008;8:2561-2568. [Link] [DOI:10.3923/jas.2008.2561.2568]
29. Hamidi Milani R, Zarabadipour H, Shahnazi R. An adaptive robust controller for time delay maglev transportation systems. Communications in Nonlinear Science and Numerical Simulation. 2012;17(12):4792-4801. [Link] [DOI:10.1016/j.cnsns.2012.04.018]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |