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Aircraft failure detection and identification over an extended flight envelope using an artificial immune system

Published online by Cambridge University Press:  27 January 2016

J. Davis
Affiliation:
West Virginia University, West Virginia, USA

Abstract

An integrated artificial immune system-based scheme that can operate over extended areas of the flight envelope is proposed in this paper for the detection and identification of a variety of aircraft sensor, actuator, propulsion, and structural failures/damages. A hierarchical multi-self strategy has been developed in which different self configurations are selected for detection and identification of specific abnormal conditions. Data collected using a motion-based flight simulator were used to define the self for a wide area of the flight envelope and to test and validate the scheme. The aircraft model represents a supersonic fighter, including model-following direct adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The proposed detection scheme achieves low false alarm rates and high detection and identification rates for all the categories of failures considered.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2011 

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