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 journalArticlepeer-review

65 Scopus citations

Abstract

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 languageEnglish
Pages (from-to)113-121
Number of pages9
JournalNeurocomputing
Volume227
DOIs
StatePublished - 1 Mar 2017

Keywords

  • Magneticlevitation system
  • Neural network
  • Neurocontrol
  • Stability

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