Model-based diagnosis of hybrid systems

Authors:
Sriram Narasimhan;Gautam Biswas
Affiliations:
QSS Group, NASA Ames Research Center, Moffett Field, CA;Dept. of EECS & ISIS, Vanderbilt University, Nashville, TN
Venue:
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Year:
2003

Citing 5
Cited 0

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Abstract

Recent years have seen a proliferation of embedded systems that combine a digital (discrete) supervisory controller with an analog (continuous) plant. Diagnosing faults in such hybrid systems, require techniques that are different from those used for discrete and continuous systems. In addition, these algorithms have to be deployed online to meet the real time requirements of embedded systems. This paper presents a methodology for online tracking and diagnosis of hybrid systems. We demonstrate the effectiveness of the approach with experiments conducted on the fuel transfer system of fighter aircraft.