Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/78782
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | H∞ model reduction for discrete-time Markov jump linear systems with partially known transition probabilities |
Other Titles: | H infinity model reduction for discrete-time Markov jump linear systems with partially known transition probabilities |
Author: | Zhang, L. Boukas, E. Shi, P. |
Citation: | International Journal of Control, 2009; 82(2):343-351 |
Publisher: | Taylor & Francis Ltd |
Issue Date: | 2009 |
ISSN: | 0020-7179 1366-5820 |
Statement of Responsibility: | Lixian Zhang, El-Kébir Boukas and Peng Shi |
Abstract: | In this art\icle, 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. |
Keywords: | Markov jump linear systems H1 model reduction partially known transition probabilities linear matrix inequality (LMI) |
Rights: | © 2009 Taylor & Francis |
DOI: | 10.1080/00207170802098899 |
Published version: | http://dx.doi.org/10.1080/00207170802098899 |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.