Robust Fault Detection H∞ Filter for Markovian Jump Linear Systems with Partial Information on the Jump Parameter
The present work focus on the Robust Fault Detection (RFD) problem in the Markovian Jump Linear System framework for the discrete-time domain, in which the Markov parameter θ(k) is considered not accessible. The assumption that the Markov Chain is not accessible brings a challenge where the filter d...
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Published in | IFAC-PapersOnLine Vol. 51; no. 25; pp. 202 - 207 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
2018
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Subjects | |
Online Access | Get full text |
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Summary: | The present work focus on the Robust Fault Detection (RFD) problem in the Markovian Jump Linear System framework for the discrete-time domain, in which the Markov parameter θ(k) is considered not accessible. The assumption that the Markov Chain is not accessible brings a challenge where the filter designed for the RFD should not be dependent on the Markov Chain parameter. In order to represent this kind of situation, the implementation of a Hidden Markov Chain to model the system mode θ(k) and the estimated mode θˆ(k) is used. The main result presented in this work is the design of a H∞ MJLS Robust Fault Detection filter that depends only on the estimated mode θˆ(k) obtained through LMI formulation. In order to illustrate the feasibility of the proposed solution a numerical example is also included. |
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ISSN: | 2405-8963 2405-8963 |
DOI: | 10.1016/j.ifacol.2018.11.105 |