• DocumentCode
    3399527
  • Title

    Type-2 FLS Modeling Capability Analysis

  • Author

    Wu, Dongrui ; Tan, Woei Wan

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Singapore Nat. Univ.
  • fYear
    2005
  • fDate
    25-25 May 2005
  • Firstpage
    242
  • Lastpage
    247
  • Abstract
    There has been an increasing amount of research on type-2 fuzzy logic systems (FLSs) recently. The interest is fueled by results demonstrating that type-2 fuzzy sets offer a framework for effectively solving problems where uncertainties are present A concept, known as the footprint of uncertainty (FOU), is mainly responsible for the improved modeling capability of type-2 FLSs. This paper aims at providing insight into how the extra mathematical dimension provided by the FOU differentiates type-2 FLSs from type-1 FLSs. Since the input-output relationships of both types of FLS are fixed once the parameters are selected, the analysis is performed by finding a set of equivalent type-1 sets (ET1Ss) that re-produces the input-output map of a type-2 FLS. Results are presented to demonstrate that a type-2 fuzzy system is able to model more complex input-output relationship because the ET1S changes as the input varies. The technique for converting a type-2 fuzzy set into a group of type-1 sets is also useful as it provides a framework for extending the entire wealth of type-1 fuzzy control/identification/design/analysis techniques to type-2 systems
  • Keywords
    control system analysis; control system synthesis; fuzzy control; fuzzy logic; fuzzy set theory; control analysis; control design; control identification; footprint of uncertainty; input-output relationship; problem solving; type-1 fuzzy control; type-2 FLS modeling capability analysis; type-2 fuzzy logic systems; type-2 fuzzy sets; Control systems; Decision making; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Nonlinear control systems; Performance analysis; Robot control; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
  • Conference_Location
    Reno, NV
  • Print_ISBN
    0-7803-9159-4
  • Type

    conf

  • DOI
    10.1109/FUZZY.2005.1452400
  • Filename
    1452400