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Fault detection and diagnosis of aircraft actuators using fuzzy-tuning IMM filter

机译:模糊IMM滤波器在飞机执行器故障检测与诊断中的应用

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摘要

This paper proposes a new interacting multiple model (IMM) filter for actuator fault detection. Since each individual filter of the IMM filter uses the combined information of the estimation values from all the operating filters, it can effectively estimate system parameter variations, thereby it can diagnose the actuator damage with an unknown magnitude. In this study, to diagnose the actuator failure fast and accurately, fuzzy logic is used to tune a transition probability among multiple models. This makes the fault detection process smooth and reduces the possibility of false fault detection. Also, a discrete fault tolerant command tracker is derived to cope with actuator damages. To validate the performance of the proposed fault detection and diagnosis (FDD) algorithm, numerical simulations are performed for a high performance aircraft system.
机译:本文提出了一种用于执行器故障检测的新型交互多模型(IMM)滤波器。由于IMM滤波器的每个单独的滤波器都使用来自所有运行滤波器的估计值的组合信息,因此它可以有效地估计系统参数变化,从而可以诊断未知大小的执行器损坏。在这项研究中,为了快速,准确地诊断执行器故障,使用模糊逻辑来调整多个模型之间的转换概率。这使故障检测过程变得顺畅,并减少了错误故障检测的可能性。此外,派生了一个离散的容错命令跟踪器来应对执行器损坏。为了验证所提出的故障检测与诊断(FDD)算法的性能,对高性能飞机系统进行了数值模拟。

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