• DocumentCode
    1233885
  • Title

    Observer-Based Fast Rate Fault Detection for a Class of Multirate Sampled-Data Systems

  • Author

    Zhong, Maiying ; Ye, Hao ; Ding, Steven X. ; Wang, Guizeng

  • Author_Institution
    Dept. of Autom., Tsinghua Univ., Beijing
  • Volume
    52
  • Issue
    3
  • fYear
    2007
  • fDate
    3/1/2007 12:00:00 AM
  • Firstpage
    520
  • Lastpage
    525
  • Abstract
    This note deals with the problem of observer-based fast rate fault detection for a class of multirate sampled-data (MSD) systems. Applying a lifting technique, a linear time-invariant (LTI) representation with slow sampling period is firstly obtained for the MSD systems and, based on this, an observer-based fault detection filter is considered as a residual generator. Then an optimization fault detection approach for LTI systems is modified to the residual generation for the MSD systems and, by solving a discrete-time Algebraic Riccati equation, a family of optimal solutions with causality constraint can be obtained. An inverse lifting operation on the generated residual implements its fast rate. The residual evaluation problem is also considered. A numerical example is finally given to illustrate the effectiveness of the proposed design techniques
  • Keywords
    Riccati equations; discrete time systems; fault diagnosis; linear systems; observers; sampled data systems; discrete time algebraic Riccati equation; inverse lifting technique; linear time-invariant representation; multirate sampled data system; observer based fast rate fault detection; Analog-digital conversion; Automatic control; Automation; Constraint optimization; Control engineering education; Digital filters; Fault detection; Fault diagnosis; Riccati equations; Sampling methods; Fast rate; fault detection; multirate; observer-based; sampled-data system;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2006.890488
  • Filename
    4132921