• DocumentCode
    3297190
  • Title

    Robust H filtering for nonlinear uncertain systems using state-dependent riccati equation technique

  • Author

    Beikzadeh, Hossein ; Taghirad, Hamid D.

  • Author_Institution
    Adv. Robot. & Automated Syst. (ARAS), K.N. Toosi Univ. of Technol., Tehran, Iran
  • fYear
    2009
  • fDate
    15-18 Dec. 2009
  • Firstpage
    4438
  • Lastpage
    4445
  • Abstract
    The standard state-dependent Riccati equation (SDRE) filter, which is set up by direct SDC parameterization, demands complete knowledge of the system model, and the disturbance inputs characteristics. However, this inherent dependency can severely degrade its performance in practical applications. In this paper, based on the H¿ norm minimization criterion, a robust SDRE filter is proposed to effectively estimate the states of nonlinear uncertain systems exposed to unknown disturbance inputs. Considering a Lipschitz condition on the chosen SDC form, we guarantee fulfillment of a modified H¿ performance index by the proposed filter. The effectiveness of the robust SDRE filter is demonstrated through numerical simulations where it brilliantly outperforms the usual SDRE filters in presence of model uncertainties as well as process and measurement noises.
  • Keywords
    H¿ control; Riccati equations; filtering theory; nonlinear control systems; robust control; uncertain systems; H¿ norm minimization criterion; Lipschitz condition; nonlinear uncertain systems; numerical simulations; robust H¿ filtering; robust SDRE filter; state dependent Riccati equation technique; Computational modeling; Differential algebraic equations; Filtering; Noise robustness; Nonlinear equations; Nonlinear filters; Observability; Observers; Riccati equations; Uncertain systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
  • Conference_Location
    Shanghai
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-3871-6
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2009.5399746
  • Filename
    5399746