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Research of FDI for Artificial Neural Network Failure Detection Method Based on Model Residual

机译:基于模型残差的人工神经网络故障检测方法的FDI研究

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FDI (Failure detection and isolation )is widely used in field of flight control, because the failure detection method base on mathematic model has the shortness that the precision of the failure detection method based on linear model depends on accuracy of the mathematic model in some degree, the FDI method based on neural network overcomes this shortness. In this paper hierarchy neural network is used to simply the structure of network and improve the performance of network according to the failure tree analysis and the research based on neural network FDI method to one kind UAV is done. Simulation in MATLAB is done to testify to this method.
机译:FDI(故障检测与隔离)在飞行控制领域得到了广泛的应用,因为基于数学模型的故障检测方法的不足之处在于,基于线性模型的故障检测方法的精度在一定程度上取决于数学模型的精度。 ,基于神经网络的FDI方法克服了这种不足。本文采用层次神经网络,通过故障树分析,简化了网络的结构,提高了网络的性能,并完成了基于神经网络FDI方法对一种无人机的研究。在MATLAB中进行了仿真以证明该方法。

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