• DocumentCode
    189035
  • Title

    A robust unscented fusion filter using fuzzy adaptation rule

  • Author

    Chul Woo Kang ; Chan Park

  • Author_Institution
    Autom. & Syst. Res. Inst., Seoul Nat. Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    24-27 June 2014
  • Firstpage
    1373
  • Lastpage
    1378
  • Abstract
    This paper presents a new robust estimation approach for nonlinear systems. Former approaches to robust nonlinear estimation such as the unscented H ∞ filter(UHF) [1] perform well on in disturbed nonlinear systems. However, with regard to undisturbed systems, the performance of robust nonlinear filters has proven inferior to that of conventional nonlinear filters. In this paper, a new filter is proposed which performs well on both disturbed and undisturbed systems by integrating a UHF and an unscented Kalman filter (UKF). The proposed filter uses a hybrid filter structure for the proper integration of the two local filters; a fuzzy-based mode adaptation rule is also implemented to improve performance.
  • Keywords
    Kalman filters; fuzzy set theory; nonlinear control systems; nonlinear estimation; nonlinear filters; robust control; UHF; disturbed nonlinear systems; fuzzy adaptation rule; fuzzy-based mode adaptation rule; nonlinear systems; robust estimation approach; robust nonlinear estimation; robust unscented fusion filter; unscented Kalman filter; Estimation; Filtering algorithms; Filtering theory; Finite impulse response filters; Kalman filters; Nonlinear filters; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2014 European
  • Conference_Location
    Strasbourg
  • Print_ISBN
    978-3-9524269-1-3
  • Type

    conf

  • DOI
    10.1109/ECC.2014.6862320
  • Filename
    6862320