Artificial Immune System – Based Aircraft Failure Evaluation over Extended Flight Envelope

摘要: This paper describes the design, development, and flight-simulation testing of an artificial-immune-system-based approach for evaluation different aircraft subsystem failures/damages. The consists estimation magnitude/severity failure prediction achievable states, leading to overall assessment effects on reducing flight envelope. A supersonic fighter model is used, which includes model-following adaptive control laws based nonlinear dynamic inversion artificial neural network augmentation. Data collected from a motion-based simulator were used define self wide area envelope test validate proposed approach. Example results are presented failure-magnitude flight-envelope-reduction abnormal conditions affecting sensors, actuators, engine, wing structure. Successful detection identification assumed before evaluation. show capabilities scheme evaluate severity predict reduction in general manner.