• DocumentCode
    434580
  • Title

    Fuzzy hyperbolic H filter design for a class of nonlinear continuous-time dynamic systems

  • Author

    Lun, Shuxian ; Zhang, Huaguang ; Liu, Derong

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    1
  • fYear
    2004
  • fDate
    14-17 Dec. 2004
  • Firstpage
    225
  • Abstract
    This paper studies fuzzy hyperbolic H filter for signal estimation of nonlinear continuous-time systems with unknown bounded disturbances. The fuzzy hyperbolic model (FHM) is a universal approximator, and can be used to establish models for unknown complex systems. Furthermore, the main advantage of using the FHM over the Takagi-Sugeno fuzzy model are that no premise structure identification is needed and no completeness design of premise variables space is needed. Also an FHM is a kind of valid global description and nonlinear model in nature. First, FHM is proposed to represent the state-space model for nonlinear continuous-time systems. Next, we design a stable fuzzy H filter based on the FHM, which assures asymptotic stability and a prescribed H index for the filtering error system. A sufficient condition for the existence of such a filter is established through seeking the feasible solutions of a linear matrix inequality (LMI). Under the position and the dimension criteria, a new LMI condition is obtained to reduce the conservativeness for the analysis and design of fuzzy H filler based on extended ε-block and λ-block and the corresponding equivalent forms. Simulation examples arc provided to illustrate the design procedure of the proposed method.
  • Keywords
    H control; continuous time systems; filtering theory; fuzzy control; large-scale systems; linear matrix inequalities; nonlinear dynamical systems; state-space methods; Takagi-Sugeno fuzzy model; fuzzy hyperbolic H filter; linear matrix inequality; nonlinear continuous-time dynamic system; state-space model; unknown bounded disturbances; unknown complex system; Asymptotic stability; Estimation; Filtering; Fuzzy systems; Linear matrix inequalities; Noise robustness; Nonlinear filters; Nonlinear systems; Signal design; Takagi-Sugeno model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2004. CDC. 43rd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-8682-5
  • Type

    conf

  • DOI
    10.1109/CDC.2004.1428634
  • Filename
    1428634