• DocumentCode
    1694532
  • Title

    On the combination of fuzzy models

  • Author

    Kumar, Mohit ; Stoll, Norbert ; Thurow, Kerstin ; Stoll, Regina

  • Author_Institution
    Center for Life Sci. Autom., Rostock, Germany
  • fYear
    2011
  • Firstpage
    322
  • Lastpage
    326
  • Abstract
    The combination of fuzzy models could be an effective way to improve system performance. This text proposes a fuzzy approach to the combination of fuzzy models, i.e., the different fuzzy models are combined using a fuzzy rule-based model. The combining fuzzy model is identified using an algorithm that is stable towards disturbances. The combination approach provides simultaneously the benefits of the individual components and thus improves overall performance. The combination scheme could be used to resolve the issue of choice of performance deciding parameters (e.g. learning rate).
  • Keywords
    fuzzy set theory; fuzzy approach; fuzzy models combination; fuzzy rule based model; Adaptation models; Data models; Indexes; Measurement uncertainty; Nonlinear systems; Robustness; Stability criteria;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2011 IEEE Conference on
  • Conference_Location
    Trieste
  • ISSN
    2161-8070
  • Print_ISBN
    978-1-4577-1730-7
  • Electronic_ISBN
    2161-8070
  • Type

    conf

  • DOI
    10.1109/CASE.2011.6042461
  • Filename
    6042461