A sequential failure detection approach and the identification of failure parameters

Toshio Yoshimura, Keigo Watanabe, Katsunobu Konishi, Takashi Soeda

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


This paper is concerned with the problem of a failure diagnosis for a discrete-time system with parametric failure, in which the occurrence time and mode of parametric failure cannot be estimated in advance. The failure diagnosis system which is proposed consists of three parts: (i) a normal mode filter, (ii) a detector for anomaly states, and (iii) an adaptive extended Kalman filter. The normal mode filter is called the optimal Kalman filter and transports the information of its innovation sequence to the detector. The detector which is based on the SPRT approach detects anomaly states affected by the parametric failure. The adaptive extended Kalman filter estimates simultaneously system parameters and the states under the failure mode. The adaptive procedure is directed by increasing the calculated covariance on the basis of hypothesis tests for the estimation errors of unknown parameters. Numerical results for a simple plant model illustrate the effectiveness of the proposed failure diagnosis system.

Original languageEnglish
Pages (from-to)827-836
Number of pages10
JournalInternational Journal of Systems Science
Issue number7
Publication statusPublished - Jul 1979
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications


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