Control and robust stabilization at unstable equilibrium by fractional controller for magnetic levitation systems

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Ataşlar-Ayyıldız B., KARAHAN O. , YILMAZ S.

Fractal and Fractional, vol.5, no.3, 2021 (Journal Indexed in SCI Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 5 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.3390/fractalfract5030101
  • Title of Journal : Fractal and Fractional
  • Keywords: Fractional order fuzzy control, Fractional order PID, Fractional order sliding mode, GWO-PSO, Maglev system


© 2021 by the authors. Li-censee MDPI, Basel, Switzerland.The problem of control and stabilizing inherently non-linear and unstable magnetic levitation (Maglev) systems with uncertain equilibrium states has been studied. Accordingly, some sig-nificant works related to different control approaches have been highlighted to provide robust control and enhance the performance of the Maglev system. This work examines a method to control and stabilize the levitation system in the presence of disturbance and parameter variations to mini-mize the magnet gap deviation from the equilibrium position. To fulfill the stabilization and disturbance rejection for this non-linear dynamic system, the fractional order PID, fractional order sliding mode, and fractional order Fuzzy control approaches are conducted. In order to design the suit-able control outlines based on fractional order controllers, a tuning hybrid method of GWO–PSO algorithms is applied by using the different performance criteria as Integrated Absolute Error (IAE), Integrated Time Weighted Absolute Error (ITAE), Integrated Squared Error (ISE), and Integrated Time Weighted Squared Error (ITSE). In general, these objectives are used by targeting the best tuning of specified control parameters. Finally, the simulation results are presented to determine which fractional controllers demonstrate better control performance, achieve fast and robust stabil-ity of the closed-loop system, and provide excellent disturbance suppression effect under nonlinear and uncertainty existing in the processing system.