• DocumentCode
    2908355
  • Title

    Fuzzy modelling of nonlinear systems for stability analysis based on piecewise quadratic Lyapunov functions

  • Author

    Shirani, Farshad ; Araabi, Babak Nadjar ; Yazdanpanah, Mohammad Javad

  • Author_Institution
    Control & Intell. Process. Center of Excellence, Univ. of Tehran, Tehran
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    2230
  • Lastpage
    2235
  • Abstract
    This paper presents a constructive Takagi-Sugeno fuzzy modeling method for a general class of nonlinear systems. This method is particularly suitable for stability analysis based on piecewise quadratic Lyapunov functions. The modeling error is appropriately inserted into the model and an algorithm is proposed to automatically determine the model parameters to keep the modeling error smaller than a desired upper bound. Based on the constructed fuzzy model, exponential stability analysis is performed and the stability constraints are transformed into linear matrix inequalities. Modeling error is also included in the stability analysis to validate the results for the original nonlinear system. The way to utilize the modeling method and stability analysis to systematically find a Lyapunov function for a nonlinear system is demonstrated via an example and the potential capability of the method in estimating the domain of attraction is discussed.
  • Keywords
    Lyapunov methods; asymptotic stability; fuzzy control; linear matrix inequalities; nonlinear control systems; piecewise polynomial techniques; constructive Takagi-Sugeno fuzzy modeling method; exponential stability analysis; fuzzy modelling; linear matrix inequalities; nonlinear systems; piecewise quadratic Lyapunov function; stability analysis; Direction of arrival estimation; Fuzzy systems; Java; Linear matrix inequalities; Lyapunov method; Nonlinear systems; Power system modeling; Stability analysis; Takagi-Sugeno model; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-1818-3
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2008.4630679
  • Filename
    4630679