Sensor Fault Estimation Filter Design for Discrete-time Linear Time-varying Systems

Q2 Computer Science 自动化学报 Pub Date : 2014-10-01 DOI:10.1016/S1874-1029(14)60365-7
Zhen-Hua WANG , Mickael RODRIGUES , Didier THEILLIOL , Yi SHEN
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引用次数: 13

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 minimum-variance 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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离散线性时变系统的传感器故障估计滤波器设计
针对一类离散线性时变系统,提出了一种传感器故障诊断方法。本文首先将传感器故障作为辅助状态变量,将所考虑的系统表述为广义系统表示。在广义系统模型的基础上,利用最小方差原理设计了能同时估计状态和传感器故障量的故障估计滤波器。然后,利用所提出的一组故障估计滤波器提出了一种故障诊断方案。本文的新颖之处在于提出了一种不考虑故障动态假设的离散LTV系统传感器故障诊断方法。该方法的另一个优点是能够在存在过程噪声和测量噪声的情况下检测、隔离和估计传感器故障。仿真结果验证了该方法的有效性。
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来源期刊
自动化学报
自动化学报 Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
4.80
自引率
0.00%
发文量
6655
期刊介绍: ACTA AUTOMATICA SINICA is a joint publication of Chinese Association of Automation and the Institute of Automation, the Chinese Academy of Sciences. The objective is the high quality and rapid publication of the articles, with a strong focus on new trends, original theoretical and experimental research and developments, emerging technology, and industrial standards in automation.
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