Robust Fault Detection H∞ Filter for Markovian Jump Linear Systems with Partial Information on the Jump Parameter

• Published in: IFAC-PapersOnLine Vol. 51; no. 25; pp. 202 - 207
• Main Authors: Carvalho, Leonardo de Paula, Oliveira, André Marcorin de, Valle Costa, Oswaldo Luiz do
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2018
• Subjects: Hidden Markov Chain; H∞ Filtering; MJLS; Robust Fault Detection; MJLS; H∞ Filtering; Hidden Markov Chain; Robust Fault Detection
• ISSN: 2405-8963; 2405-8963
• DOI: 10.1016/j.ifacol.2018.11.105

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.