• DocumentCode
    3706957
  • Title

    Nonlinear system identification based on modified ANFIS

  • Author

    José Kleiton Ewerton da Costa Martins;Fábio Meneghetti Ugulino de Araújo

  • Author_Institution
    Universidade Federal do Rio Grande do Norte, Departamento de Engenharia da Computaç
  • Volume
    1
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    588
  • Lastpage
    595
  • Abstract
    This article aims to present the nonlinear system identification by the method of modified ANFIS. The modified ANFIS is a structure proposed that is based on the traditional structure of ANFIS with some modifications as shown in the article. The importance of the choice of method parameters and its influence on the system will be discussed. For this, the identification of a coupled system of tanks with nonlinear dynamics is performed. System identification will be performed by changing the inputs and order of the consequent model and then will perform a review of the systems. The results confirm the simplicity of modified ANFIS in comparison with the traditional ANFIS while have good performance in the identification of nonlinear systems.
  • Keywords
    "Training","Biological neural networks","Computational modeling","Fuzzy systems","Software","Nonlinear dynamical systems"
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (ICINCO), 2015 12th International Conference on
  • Type

    conf

  • Filename
    7350527