Modelling of a Nonlinear Fuzzy Three-Input PID Controller and Its Simulation and Experimental Realization

Sain, Debdoot; Mohan, B.M.

doi:10.1080/02564602.2020.1773326

Cited by 14 publications

(1 citation statement)

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“…Moreover, to show the superiority of the proposed controller, the simulations and comparisons were performed in the presence of different operation conditions. In another work, modelling of three-input fuzzy PID controller was realized by Sain and Mohan [38] for controlling the unstable nonlinear Maglev system. In the paper, the parameters of the proposed fuzzy PID controller were optimized with GA based on the cost function, including the error and control effort.…”

Section: Introductionmentioning

confidence: 99%

Control and Robust Stabilization at Unstable Equilibrium by Fractional Controller for Magnetic Levitation Systems

2021

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The problem of control and stabilizing inherently non-linear and unstable magnetic levitation (Maglev) systems with uncertain equilibrium states has been studied. Accordingly, some significant 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 minimize 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 suitable 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 stability of the closed-loop system, and provide excellent disturbance suppression effect under nonlinear and uncertainty existing in the processing system.

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Section: Introductionmentioning

confidence: 99%