期刊
IFAC JOURNAL OF SYSTEMS AND CONTROL
卷 1, 期 -, 页码 13-23出版社
ELSEVIER
DOI: 10.1016/j.ifacsc.2017.05.002
关键词
Filtering; Stochastic control; Robust control; Hidden Markov models; Linear matrix inequality; Fault-tolerant systems
资金
- Sao Paulo Research Foundation-FAPESP [2015/09912-8]
- Brazilian National Research Council-CNPq [304091/20146]
- FAPESP/BG Brasil, through the Research Center for Gas Innovation, FAPESP [2014/50279-4]
- project INCT [CNPq-465755/2014-3, FAPESP-2014/50851-0]
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.
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