This paper describes the design, development, and flight simulation testing of an artificial immune system-based approach for evaluation of different sensor, actuator, propulsion, and structural failures/damages. The evaluation is performed with the estimation of the magnitude/severity of the failure and the prediction of the achievable states leading to an overall assessment of the effects of the failure on reducing the flight envelope of the aircraft. A supersonic fighter model is used, which includes model-following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. 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 proposed approach. The results show the capabilities of the artificial immune system-based scheme to predict or estimate the reduction of the flight envelope in a general manner
