• DocumentCode
    3720745
  • Title

    ANFIS data driven modeling and real-time Fuzzy Logic Controller test for a Two Tanks Hydraulic System

  • Author

    L. A. Torres-Salomao;J. Anzurez-Marin;J. M. Orozco-Sixtos;S. Ram?rez-Zavala

  • Author_Institution
    Automatic Control and Systems Engineering Department, The University of Sheffield, United Kingdom
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic Controller optimized with Genetic Algorithms (GA). The controller was designed and tested in simulation with the obtained ANFIS model and validated in real-time with the actual TTHS. Obtained model shows an accurate and adequate description of the real system, useful for many applications that require a non-linear functioning representation of the TTHS. The designed controller also demonstrates excellent performance by being able to follow diverse shaped references. This work successfully demonstrates the utility of soft-computing techniques in their application to real world industrial complex systems.
  • Keywords
    "Mathematical model","Data models","Fuzzy logic","Genetic algorithms","Training","Testing","Artificial neural networks"
  • Publisher
    ieee
  • Conference_Titel
    Evolving and Adaptive Intelligent Systems (EAIS), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/EAIS.2015.7368778
  • Filename
    7368778