Improved adaptive fuzzy backstepping control of a magnetic levitation system based on Symbiotic Organism Search

Display Omitted Improved adaptive fuzzy backstepping controller for magnetic levitation system.Adaptive fuzzy law for systems with partially known or uncertain input nonlinearity.Adaptation law obtained with Ljapunov analysis.Initial adaptive and control parameters initialized with Symbiotic Organism Search.Theoretical verification based on simulation study and laboratory application. Magnetic levitation systems have become very important in many applications. Due to their instability and high nonlinearity, such systems pose a challenge to many researchers attempting to design high-performance and robust tracking control. This paper proposes an improved adaptive fuzzy backstepping control for systems with uncertain input nonlinear function (uncertain parameters and structure), and applies it to a magnetic levitation system, which is a typical representative of such systems. An adaptive fuzzy system is used to approximate unknown, partially known or uncertain input nonlinear functions of a magnetic levitation system. An adaptation law is obtained based on Ljapunov analysis in order to guarantee closed-loop stability and good tracking performance. Initial adaptive and control parameters have been initialized with Symbiotic Organism Search optimization algorithm, due to strong non-linearity and instability of the magnetic levitation system. The theoretical background of the proposed control method is verified with a simulation study and implementation on a laboratory experimental application.

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