Research Repository

H-infinity model reduction for discrete-time Markov jump linear systems with partially known transition probabilities

Zhang, Lixian and Boukas, El-Kebir and Shi, Peng (2009) H-infinity model reduction for discrete-time Markov jump linear systems with partially known transition probabilities. International Journal of Control, 82 (2). pp. 343-351. ISSN 0020-7179

Full text for this resource is not available from the Research Repository.

Abstract

In this article, the H∞ model reduction problem for a class of discrete-time Markov jump linear systems (MJLS) with partially known transition probabilities is investigated. The proposed systems are more general, relaxing the traditional assumption in Markov jump systems that all the transition probabilities must be completely known. A reduced-order model is constructed and the LMI-based sufficient conditions of its existence are derived such that the corresponding model error system is internally stochastically stable and has a guaranteed H∞ performance index. A numerical example is given to illustrate the effectiveness and potential of the developed theoretical results.

Item Type: Article
Uncontrolled Keywords: ResPubID7678, Markov jump linear systems, H∞ model reduction, partially known transition probabilities, linear matrix inequality (LMI)
Subjects: SEO Classification > 970109 Expanding Knowledge in Engineering
Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
FOR Classification > 0199 Other Mathematical Sciences Information Systems
Related URLs:
Depositing User: VUIR
Date Deposited: 14 Jun 2011 02:02
Last Modified: 01 Dec 2014 00:42
URI: http://vuir.vu.edu.au/id/eprint/4734
DOI: 10.1080/00207170802098899
ePrint Statistics: View download statistics for this item
Citations in Scopus: 17 - View on Scopus

Repository staff only

View Item View Item

Search Google Scholar