Sliding Mode Control with Gain-Scheduled for Magnetic Levitation System

Rudi Uswarman, Swadexi Istiqphara, Denny Hidayat T.N.

Abstract


This paper presents a study of controlling magnetic levitation object using conventional sliding mode control (CSMC) and sliding mode control (SMC) with gain-scheduled. SMC with gain-scheduled aims to improve the robustness of the control system from disturbance. The CSMC simulation results show that output can follow the set point if there is no interference, but if the disturbance happens then there is overshoot and undershoot of 0.034 mm and 0.07 mm for disturbance 10 ∗ sin (𝑡) and 20 ∗ sin (𝑡). Then SMC with gain-scheduled shows excellent performance because the output can follow the reference even if it got disturbance of 10 ∗ sin (𝑡) and 20 ∗ sin (𝑡).

Keywords


Magnetic levitation; Sliding mode control; Gain-scheduled, Disturbance; Performance

Full Text:

PDF

References


N. Shirakuni, “SCMAGLEV: The Japanese Technology That Will Revolutionize Intercity Transport,” accessed on 26 May 2019, available at: Google

M. A. Akram, et al.,”Sliding Mode Control for Electromagnetic Levitation System Based on Feedback Linearization.” Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, pp, 78-82, 2015, doi: 10.1109/RoboMech.2015.7359502.

A. R. Moreno, C. C. Condor,”PD and PID control of a Maglev System an Experimental Comparative Study.” International Conference on Electronics, Electrical Engineering and Computing, 2017, doi: 10.1109/INTERCON.2017.8079678.

N. Magaji, J.L. Sumaila,”Fuzzy Logic Controller for Magnetic Levitation System.” International Conference on Adaptive Science and Technology, 2014, doi: 10.1109/ICASTECH.2014.7068112.

B. Tandon, S. Kaur, A. Kaira,”Stability Analysis of Feedback Linearized Magnetic Levitation System using sum of squares Method.” International Conference on Signal Processing, Computing and Control, pp. 420-424, 2017, doi: 10.1109/ISPCC.2017.8269715.

H. Ahmad, et al., “Design of LQR Controller for a Nonlinear Maglev System.” Journal of Engineering and Higher Technology, pp. 1-8, 2017, available at: Google.

S. Zhao, X. Gao,”Neural Network Adaptive State Feedback Control of a Magnetic Levitation System.” Chinese Control and Decision Conference, pp 1602-1605, 2014, doi: 10.1109/CCDC.2014.6852423.

A. Antic, et al.,”Simulation Model of Magnetic Levitation Based on NARX Neural Networks.” International Journal Intelligent Systems and Applications, pp. 25-32, 2013, available at: Google Scholar.

M.B. Milovanovic, et al., “Neural Network based on Orthogonal Polynomials Applied in Magnetic Levitation.” Research Journal ELEKTRONIKA IR ELEKTROTECHNIKA, vol. 23, pp. 24-29, 2017, doi: 10.5755/j01.eie.23.3.13167.

A.A. Khandekar, B.M. Patre,”Discrete sliding mode control for robust tracking of time-delay systems,” Systems Science & Control Engineering Journal, pp. 457-464, 2014, doi: 10.1080/21642583.2014.913214.

Y. Sun, et al., “Nonlinear dynamic modelling and fuzzy sliding-mode controlling of electromagnetic levitation system of low speed maglev train.” Journal of Vibroengineering, pp. 328-342, 2017, doi: 10.21595/jve.2017.17499.

R. Uswarman, A.I. Chayadi, O. Wahyunggoro,”Design and Implementation of a Magnetic Levitation System Controller using Global Sliding Mode Control.” Journal of Mechatronics, Electrical Power, and Vehicular Technology, vol. 5, pp. 17-26, 2014, doi: 10.14203/j.mev.2014.v5.17-26.

S. U. Din, et al.,“Smooth super-twisting sliding mode control for the class of underactuated systems.” PLOS ONE Journal, 2018, doi: 10.1371/journal.pone.0203667.

S. Vaidyanathan, C. Volos, Advances and Applications in Nonlinear Control System, 1st ed. Switzerland, Springer, 2016, available at: Google Scholar.

M.A. Bafghi, A. Delavarkhalafi,”Designing a new sliding mode control for stochastic system with packet losses.” International Journal of Control, pp. 1-6, 2019, doi: 10.1080/00207179.2018.1551627.

M. Idrees, S. Ullah, S. Muhammad,”Sliding mode control design for stabilization of underactuated mechanical systems.” Advances in Mechanical Engineering: SAGE Journals, pp. 1-10, 2019, doi: 10.1177/1687814019842712.

Y. Yueneng, Y. Ye,”Bacstepping sliding mode control for uncertain strict-feedback nonlinear systems using neural-network-based adaptive gain scheduling.” Journal of Systems Engineering and Electronics, vol. 29, pp. 580-586, 2018, doi: 10.21629/JSEE.2018.03.15.




DOI: http://dx.doi.org/10.26555/jiteki.v5i1.13223

Article Metrics

Abstract view : 0 times
PDF - 0 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Universitas Ahmad Dahlan

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Jurnal Ilmiah Teknik Elektro Komputer dan Informatika
ISSN 2338-3070 (print) | 2338-3062 (online)
Organized by Electrical Engineering Department - Universitas Ahmad Dahlan
Published by Universitas Ahmad Dahlan
Website: http://journal.uad.ac.id/index.php/jiteki
Email 1: jiteki@ee.uad.ac.id
Email 2: alfianmaarif@ee.uad.ac.id
Office Address: Kantor Program Studi Teknik Elektro, Lantai 6 Sayap Barat, Kampus 4 UAD, Jl. Ringroad Selatan, Tamanan, Kec. Banguntapan, Bantul, Daerah Istimewa Yogyakarta 55191, Indonesia