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H-infinity-filtering for Markov jump linear systems with partial information on the jump parameter

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Author(s):
de Oliveira, A. M. ; Costa, O. L., V
Total Authors: 2
Document type: Journal article
Source: IFAC JOURNAL OF SYSTEMS AND CONTROL; v. 1, p. 11-pg., 2017-09-30.
Abstract

We study in this work the H-infinity-filtering problem in a partial information context. We suppose that the state of the Markov chain theta(k) is not available to the filter, but only an estimation coming from a detector and represented by (theta) over cap (k). We present two main results related to the synthesis of filters that depend only on (theta) over cap (k) such that the H-infinity norm in relation to the estimation error is limited: the case in which the transition and detection probabilities are not exactly known, but belong to distinct convex sets; and the Bernoulli case in which we derive necessary and sufficient conditions for the filter synthesis. All the results are given in terms of linear matrix inequalities and are illustrated by two numerical examples of systems prone to faults. (c) 2017 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 15/09912-8 - Estimating and control of Markov jump linear systems with partial observation of the operation mode
Grantee:André Marcorin de Oliveira
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 14/50279-4 - Brasil Research Centre for Gas Innovation
Grantee:Julio Romano Meneghini
Support Opportunities: Research Grants - Research Centers in Engineering Program
FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
Grantee:Marco Henrique Terra
Support Opportunities: Research Projects - Thematic Grants