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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Format | Journal Article |
Language | English |
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2018
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Abstract | 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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AbstractList | 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. |
Author | Carvalho, Leonardo de Paula Oliveira, André Marcorin de Valle Costa, Oswaldo Luiz do |
Author_xml | – sequence: 1 givenname: Leonardo de Paula surname: Carvalho fullname: Carvalho, Leonardo de Paula email: carvalho.lp@usp.br organization: Universidade de São Paulo, São Paulo, SP, Brazil – sequence: 2 givenname: André Marcorin de surname: Oliveira fullname: Oliveira, André Marcorin de email: marcorin@usp.br organization: Universidade de São Paulo, São Paulo, SP, Brazil – sequence: 3 givenname: Oswaldo Luiz do surname: Valle Costa fullname: Valle Costa, Oswaldo Luiz do email: oswaldo@lac.usp.br organization: Universidade de São Paulo, São Paulo, SP, Brazil |
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Cites_doi | 10.1049/ip-cta:20045085 10.1109/MCS.2002.1035218 10.1016/S1474-6670(17)37370-6 10.1016/j.sigpro.2010.04.007 10.1002/rnc.1610 10.1080/00207179408923072 10.1109/TCST.2009.2026285 10.1016/j.automatica.2018.01.034 10.1109/ACCESS.2017.2735027 10.1016/j.ifacsc.2017.05.002 10.1109/9.654895 10.1137/S0363012903434753 10.1016/S0098-1354(02)00160-6 10.1016/S0167-6911(99)00035-3 10.1109/23.531786 10.1109/CDC.2015.7402775 |
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Keywords | MJLS H∞ Filtering Hidden Markov Chain Robust Fault Detection |
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SubjectTerms | Hidden Markov Chain H∞ Filtering MJLS Robust Fault Detection |
Title | Robust Fault Detection H∞ Filter for Markovian Jump Linear Systems with Partial Information on the Jump Parameter |
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