Input-output systems robust nonlinear fault diagnosis

Author

Vemuri, Arun T. ; Polycarpou, Marios M.

Author_Institution

Dept. of Engine & Vehicle Res., Southwest Res. Inst., San Antonio, TX, USA

Volume

2

fYear

1997

fDate

4-6 Jun 1997

Firstpage

927

Abstract

Describes a fault diagnosis algorithm for a class of nonlinear dynamic systems with modeling uncertainties when not all states of the system are measurable. The main idea behind this approach is to monitor the plant for any off-nominal system behavior due to faults utilizing a nonlinear online approximator with adjustable parameters. A nonlinear estimation model and learning algorithm are described so that the online approximator provides an estimate of the fault. The robustness, sensitivity, stability and performance properties of the nonlinear fault diagnosis scheme are rigorously established under certain assumptions on the failure type

Keywords

adaptive control; approximation theory; fault diagnosis; learning (artificial intelligence); nonlinear dynamical systems; parameter estimation; uncertain systems; input-output systems; learning algorithm; modeling uncertainties; nonlinear dynamic systems; nonlinear estimation model; nonlinear online approximator; off-nominal system behavior; performance properties; robust nonlinear fault diagnosis; sensitivity; stability; Condition monitoring; Ear; Engines; Fault detection; Fault diagnosis; Nonlinear dynamical systems; Redundancy; Robust stability; Robustness; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1997. Proceedings of the 1997

Conference_Location

Albuquerque, NM

ISSN

0743-1619

Print_ISBN

0-7803-3832-4

Type

conf

DOI

10.1109/ACC.1997.609662

Filename

609662