Document Type

Article

Publication Date

2014

DOI

10.2514/1.62523

Publication Title

Journal of Guidance, Control, and Dynamics

Volume

37

Issue

3

Pages

941-946

Abstract

A class of FDI (fault detection and identification) methods for bias-type actuator and sensor faults was explored from the point of view of fault identifiability. The methods use banks of Kalman-Bucy filters (KBFs) to detect faults, determine the fault pattern, and estimate the fault values. A complete characterization of conditions for identifiability of bias-type actuator faults, sensor faults, and simultaneous actuator and sensor faults was presented. It was shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have unknown biases. The fault identifiability conditions were demonstrated via numerical examples. The analytical and numerical results indicate that caution must be exercised to ensure fault identifiability for different fault patterns when using such methods.

Comments

This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States.

Original Publication Citation

Joshi, S. M., González, O. R., & Upchurch, J. M. (2014). Identifiability of additive actuator and sensor faults by state augmentation. Journal of Guidance, Control, and Dynamics, 37(3), 941-946. doi:10.2514/1.62523

ORCID

0000-0001-9503-4171 (Gonzalez)

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