Transactions of the Society of Instrument and Control Engineers
Online ISSN : 1883-8189
Print ISSN : 0453-4654
ISSN-L : 0453-4654
KDI-Based Robust Fault Detection in Presence of Nonlinear Undermodeling
Jinglu HUKousuke KUMAMARUKatsuhiro INOUEKotaro HIRASAWA
Author information

1999 Volume 35 Issue 2 Pages 200-207


This paper deals with the problems of robust fault detection using Kullback discrimination information (KDI) in presence of nonlinear undermodeling. The systems to be diagnosed are assumed to contain certain unknown nonlinear elements. The fault detection is performed by applying the KDI to a linear ARMAX model with model uncertainty, in which error due to nonlinear undermodeling is described using a group of fuzzy models with adjustable parameters. The estimate of modeling error is considered in the KDI analysis and thresholding decision for robustness realization. The effectiveness of the proposed robust fault detection scheme is examined through numerical simulations.

Content from these authors
© The Society of Instrument and Control Engineers (SICE)
Previous article Next article