Presentation
Immunity – Based Aircraft Failure Detection and Identification Using an Integrated Hierarchical Multi-Self Strategy
AIAA Guidance, Navigation, and Control Conference and Exhibit 2009
(2009)
Abstract
This paper presents the development and application of an integrated artificial immune system-based scheme for the detection and identification of a wide variety of aircraft sensor, actuator, propulsion, and structural failures/damages. The proposed approach is based on a hierarchical multi-self strategy where different self configurations are selected for the identification of specific abnormal conditions. Data collected using a motion-based flight simulator was used to define the self for a sub-region of the flight envelope. The aircraft model represents a supersonic fighter, including model-following 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 the four categories of failures considered.
Keywords
- Artificial Immune System,
- Artificial Neural Network,
- Adaptive control systems,
- Aircraft detection,
- Adaptive control law,
- Nonlinear dynamic inversion
Publication Date
July, 2009
Location
Chicago, IL
DOI
https://doi.org/10.2514/6.2009-5878
Citation Information
Hever Moncayo, M. G. Perhinschi and J. Davis. "Immunity – Based Aircraft Failure Detection and Identification Using an Integrated Hierarchical Multi-Self Strategy" AIAA Guidance, Navigation, and Control Conference and Exhibit 2009 (2009) Available at: http://works.bepress.com/hever_moncayo/40/