Robust parametric and non-parametric fault diagnosis in nonlinear input-output systems

This paper describes a fault diagnosis algorithm for a class of nonlinear dynamic systems with modeling uncertainties, using input/output measurements. Two types of faults are considered: parametric faults which characterize fault functions of known structure but unknown parameters, and non-parametr...

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Bibliographic Details
Published inProceedings of the 36th IEEE Conference on Decision and Control Vol. 5; pp. 4481 - 4482 vol.5
Main Authors Parisini, T., Polycarpou, M., Sanguineti, M., Vemuri, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1997
Subjects
Analytical models
Differential equations
Fault detection
Fault diagnosis
Input variables
Redundancy
Robustness
Uncertainty
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ISBN0780341872
9780780341876
ISSN0191-2216
DOI10.1109/CDC.1997.649672

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Summary:This paper describes a fault diagnosis algorithm for a class of nonlinear dynamic systems with modeling uncertainties, using input/output measurements. Two types of faults are considered: parametric faults which characterize fault functions of known structure but unknown parameters, and non-parametric faults where the structure of the fault function is unknown. A nonlinear estimation model with a learning algorithm is developed and the fault separability concept for parametric faults is discussed.
ISBN:0780341872
9780780341876
ISSN:0191-2216
DOI:10.1109/CDC.1997.649672