BAYESIAN SOFTWARE HEALTH MANAGEMENT FOR AIRCRAFT GUIDANCE, NAVIGATION, AND CONTROL

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Johann Schumann Timmy Mbaya Ole Mengshoel

Abstract

Modern aircraft—both piloted fly-by-wire commercial aircraft as well as UAVs—more and more depend on highly complex safety critical software systems with many sensors and computer-controlled actuators. Despite careful design and V&V of the software, severe incidents have happened due to malfunctioning software. In this paper, we discuss the use of Bayesian networks to monitor the health of the on-board software and sensor system, and to perform advanced on-board diagnostic reasoning. We focus on the development of reliable and robust health models for combined software and sensor systems, with application to guidance, navigation, and control (GN&C). Our Bayesian network-based approach is illustrated for a simplified GN&C system implemented using the open source real-time operating system OSEK/Trampoline. We show, using scenarios with injected faults, that our approach is able to detect and diagnose faults in software and sensor systems.

How to Cite

Schumann, J. ., Mbaya, T. ., & Mengshoel, . O. . (2011). BAYESIAN SOFTWARE HEALTH MANAGEMENT FOR AIRCRAFT GUIDANCE, NAVIGATION, AND CONTROL. Annual Conference of the PHM Society, 3(1). https://doi.org/10.36001/phmconf.2011.v3i1.2022
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Keywords

software health management, Bayes network, aircraft systems

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Section
Technical Papers