JOURNAL ARTICLE

Unbiased Minimum‐Variance Filter for State and Fault Estimation of Linear Time‐Varying Systems with Unknown Disturbances

Fayçal Ben HmidaKarim KhémiriJosé RagotMoncef Gossa

Year: 2010 Journal:   Mathematical Problems in Engineering Vol: 2010 (1)   Publisher: Hindawi Publishing Corporation

Abstract

This paper presents a new recursive filter to joint fault and state estimation of a linear time‐varying discrete systems in the presence of unknown disturbances. The method is based on the assumption that no prior knowledge about the dynamical evolution of the fault and the disturbance is available. As the fault affects both the state and the output, but the disturbance affects only the state system. Initially, we study the particular case when the direct feedthrough matrix of the fault has full rank. In the second case, we propose an extension of the previous case by considering the direct feedthrough matrix of the fault with an arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum‐variance (UMV) criteria. A numerical example is given in order to illustrate the proposed method.

Keywords:
Feedthrough Control theory (sociology) Fault (geology) Rank (graph theory) Filter (signal processing) Minimum-variance unbiased estimator Variance (accounting) State (computer science) Recursive filter Matrix (chemical analysis) Mathematics Computer science Engineering Algorithm Filter design Statistics Control (management) Mean squared error Artificial intelligence

Metrics

31
Cited By
6.38
FWCI (Field Weighted Citation Impact)
16
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fault Detection and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Control Systems and Identification
Physical Sciences →  Engineering →  Control and Systems Engineering

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