Experimental application of extended Kalman filtering for sensor validation

A sensor failure detection and identification scheme for a closed loop nonlinear system is described. Detection and identification tasks are performed by estimating parameters directly related to potential failures. An extended Kalman filter is used to estimate the fault-related parameters, while a...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2001-03, Vol.9 (2), p.376-380
Main Authors: Del Gobbo, D., Napolitano, M., Famouri, P., Innocenti, M.
Format: Article
Language:English
Subjects:
Algorithms
Dynamical systems
Estimates
Estimating
Failure
Failure detection
Fault detection
Filtering
Kalman filters
Logic
Nonlinear systems
Parameter estimation
Pendulums
Sensor phenomena and characterization
Sensor systems
Sensors
Software performance
Testing
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Description
Summary:A sensor failure detection and identification scheme for a closed loop nonlinear system is described. Detection and identification tasks are performed by estimating parameters directly related to potential failures. An extended Kalman filter is used to estimate the fault-related parameters, while a decision algorithm based on threshold logic processes the parameter estimates to detect possible failures. For a realistic evaluation of its performance, the detection scheme has been implemented on an inverted pendulum controlled by real-time control software. The failure detection and identification scheme is tested by applying different types of failures on the sensors of the inverted pendulum. Experimental results are presented to validate the effectiveness of the approach.
ISSN:1063-6536
1558-0865
DOI:10.1109/87.911389