Integrated Immunity-Based Framework for Aircraft Abnormal Conditions Management

Abstract

This paper presents the development of a biologically inspired generalized conceptual framework for the detection, identification, evaluation, and accommodation of aircraft subsystem abnormal conditions. The artificial immune system paradigm in conjunction with other artificial intelligence techniques, analytical tools, and heuristics are used in an attempt to provide a comprehensive solution to the problem of safely operating aircraft under abnormal flight conditions. The main concepts and foundations are established, and methodologies and algorithms for implementation are outlined. The approach addresses directly the complexity and multidimensionality of aircraft dynamic response in the context of abnormal conditions and is expected to facilitate the design of onboard augmentation systems to increase aircraft survivability, improve operation safety, and optimize performance at both normal and abnormal/upset conditions. Results obtained with an example implementation are presented to illustrate the potential of the proposed framework for producing high-performance schemes for aircraft subsystem abnormal condition detection, identification, evaluation, and accommodation.