Modeling and control with neural networks for a magnetic levitation system

José de Jesús Rubio, Lixian Zhang, Edwin Lughofer, Panuncio Cruz, Ahmed Alsaedi, Tasawar Hayat

    Research output: Contribution to journalArticle

    31 Scopus citations

    Abstract

    © 2016 Elsevier B.V. This study presents the model and control of the magnetic levitation system. The model considers the angular position of the ball, also a neural network approximates the electromagnetic parameter. The neural network controller is the combination of a nonlinear method and a neural network, also its stability is guaranteed by utilizing the Lyapunov method. The proposed controller is compared with the two stages controller for the trajectory tracking in the magnetic levitation system.
    Original languageAmerican English
    Pages (from-to)113-121
    Number of pages100
    JournalNeurocomputing
    DOIs
    StatePublished - 1 Mar 2017

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