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

机译:基于神经网络的飞控系统传感器在线故障诊断与重配置

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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与重配置方案。它基于无线电基础功能网络(RBF),该网络是通过有效的在线训练和参数优化算法设计的。使用多模型自适应技术,设计了一组自适应神经网络观测器,以约束建模不确定性和飞行控制系统中的输出耦合。该方案的性能通过自动地形跟随飞行控制系统内一架战斗机的非线性仿真得到了验证。总之,可以实现在线住宿。

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