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首页> 外文期刊>Transactions of the Institute of Measurement and Control >Fractional order unknown input filter design for fault detection of discrete fractional order linear systems
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Fractional order unknown input filter design for fault detection of discrete fractional order linear systems

机译:离散分数阶线性系统故障检测故障检测的分数未知输入滤波器设计

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摘要

In this study, a new method is introduced to design an estimator for discrete-time linear fractional order systems, which are affected by unknown disturbances. The main goal of this study is decoupling disturbance and uncertainties from the true states for discrete fractional order systems in noisy environment. The fractional Kalman filter framework is exploited to develop a robust estimator against unknown inputs (UIs) in noisy environment. The proposed filter is exploited to detect faults in fractional order systems. Simulation results illustrate the advantages of this robust filter for state estimation and fault detection of fractional order model of ultra-capacitor (UC). The robustness of the designed filter is shown in the sense of disturbance decoupling in the presence of noise.
机译:在本研究中,引入了一种新方法来设计用于离散时间线性分数阶系统的估计,这受到未知干扰的影响。 本研究的主要目标是从嘈杂环境中离散分数阶系统的真正态度解耦和不确定性。 分数卡尔曼滤波器框架被利用以在嘈杂的环境中对未知输入(UIS)进行强大的估计器。 拟议的滤波器被利用以检测分数阶系统中的故障。 仿真结果说明了超电容器(UC)分数级模型的状态估计和故障检测的强大滤波器的优点。 设计过滤器的稳健性显示在噪声存在下的干扰感。

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