Fault detection and isolation for the Bluebird test bed aircraft
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Authors
Levesque, Mario J. L.
Subjects
Fault detection and isolation
Failure detection
FDI
Sensor failure
Actuator failure
Multiple Model algorithm
Kalman filter
Failure detection
FDI
Sensor failure
Actuator failure
Multiple Model algorithm
Kalman filter
Advisors
Kaminer, Isaac I.
Date of Issue
1993-12
Date
December 1993
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
A Fault Detection and isolation (FDI) algorithm design is presented using the Multiple Model algorithm technique for the Bluebird aircraft being developed at the Naval Postgraduate School. The requirement to maintain high performance in the dynamic system of the aircraft necessitates the use of FDI techniques to detect and isolate malfunctions in the sensors and actuators of the aircraft without using hardware redundancy. The solution presented makes use of analytical redundancy in a bank of Kalman filters. Statistical tests using Bayesian theory are applied on the filter's innovations to perform the task of detection and isolation. The algorithm was developed using MATLAB software from The Math Works, Inc. The work presented in this thesis is related only to the task of FDI. The remaining task of the monitoring system, reconfiguration and continued operation by the observed plant after a failure detection, will not be addressed.
Type
Thesis
Description
Series/Report No
Department
Department of Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
104 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner.