Sensor Fault Estimation Filter Design for Discrete-time Linear Time-varying Systems
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摘要: 针对一类离散时间线性时变系统提出了一种传感器故障诊断方法.本文首先通过状态增广的方式将被研究的系统转化为描述系统的形式,并且基于该描述系统模型,采用方差最小化原则设计了一种能够同时估计系统状态和传感器故障的故障估计滤波器,然后利用一组故障估计滤波器提出了一种故障诊断方法.本文的主要贡献在于针对离散线性时变系统提出了一种不需要对故障动态进行假设的传感器故障诊断方法.所提出方法的另一个优点是该方法能够在存在过程和测量噪声的情况下实现故障检测、分离与估计.仿真结果说明了所提出方法的有效性.Abstract: This paper proposes a sensor fault diagnosis method for a class of discrete-time linear time-varying (LTV) systems. In this paper, the considered system is firstly formulated as a descriptor system representation by considering the sensor faults as auxiliary state variables. Based on the descriptor system model, a fault estimation filter which can simultaneously estimate the state and the sensor fault magnitudes is designed via a minimumvariance principle. Then, a fault diagnosis scheme is presented by using a bank of the proposed fault estimation filters. The novelty of this paper lies in developing a sensor fault diagnosis method for discrete LTV systems without any assumption on the dynamic of fault. Another advantage of the proposed method is its ability to detect, isolate and estimate sensor faults in the presence of process noise and measurement noise. Simulation results are given to illustrate the effectiveness of the proposed method.
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