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Neural Network-Based Sensor Online Fault Diagnosis and Reconfiguration for Flight Control Systems

机译:基于神经网络的传感器在线故障诊断和重新配置飞行控制系统

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摘要

A scheme for sensor online fault diagnosis and reconfiguration was proposed. It was based on the Radio Basis Function network (RBF) which was designed by efficient algorithm of on-line training and parameter optimization. Using multiple model adaptive technique, a set of adaptive neural network observers were designed to restrain modeling uncertainties and the output couple in flight control system. The performance of the scheme was validated by the nonlinear simulation for a fighter within automatic terrain following flight control system. As a conclusion, online accommodation is achieved.
机译:提出了一种传感器在线故障诊断和重新配置的方案。它基于无线电基函数网络(RBF),该网络是由高效的在线训练和参数优化算法设计的。使用多种式自适应技术,设计了一组自适应神经网络观察者,旨在抑制模型不确定性和飞行控制系统中的输出耦合。在飞行控制系统之后自动地形内的战斗机的非线性模拟验证了该方案的性能。作为一个结论,实现了在线住宿。

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