State-feedback stabilization of Markov jump linear systems with randomly observed markov states

Masaki Ogura, Ahmet Cetinkaya, Victor M. Preciado

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper we study the state-feedback stabilization of a discrete-time Markov jump linear system when the observation of the Markov chain of the system, called the Markov state, is time-randomized by another Markov chain. Embedding the Markov state into an extended Markov chain, we transform the given system with time-randomized observations to another one having the enlarged Markov state space but with so-called cluster observations of Markov states. Based on this transformation we propose linear matrix inequalities for designing stabilizing state-feedback gains for the original Markov jump linear systems. The proposed method can treat both periodic observations and many of renewaltype observations in a unified manner, which are studied in the literature using different approaches. A numerical example is provided to demonstrate the obtained result.

Original languageEnglish
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781479986842
Publication statusPublished - 2015 Jul 28
Externally publishedYes
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: 2015 Jul 12015 Jul 3

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2015 American Control Conference, ACC 2015
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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