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

机译：基于人工免疫系统的飞机故障对扩展飞行范围的评估

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This paper describes the design, development, and flight-simulation testing of an artificial-immune-system-based approach for the evaluation of different aircraft subsystem failures/damages. The evaluation consists of 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. A supersonic fighter model is used, which includes model-following adaptive control laws based on nonlinear dynamic inversion and artificial neural network augmentation. Data collected from 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. Example results are presented for failure-magnitude evaluation and flight-envelope-reduction prediction for abnormal conditions affecting sensors, actuators, engine, and wing structure. Successful failure detection and identification are assumed before evaluation. The results show the capabilities of the artiricial-immune-system-based scheme to evaluate the severity of the failure and to predict the reduction of the flight envelope in a general manner.
机译：本文介绍了一种基于人工免疫系统的方法的设计，开发和飞行模拟测试，用于评估不同的飞机子系统故障/损坏。评估包括对故障幅度/严重性的估计以及对可实现状态的预测，从而对故障对减小飞行包线的影响进行总体评估。使用了超音速战斗机模型，该模型包括基于非线性动态反演和人工神经网络扩充的模型遵循自适应控制定律。从基于运动的飞行模拟器收集的数据用于定义飞行包络线的广阔区域的自我，并测试和验证所提出的方法。给出了示例结果，用于对影响传感器，执行器，发动机和机翼结构的异常情况进行故障幅度评估和减少飞行包络预测。在评估之前，假定成功进行了故障检测和识别。结果显示了基于动脉免疫系统的方案评估故障严重程度并以一般方式预测飞行包线减少的能力。

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