Sojourn-probability-dependent control for networked switched systems under asynchronous switching
Engang Tian,
Yinghui Hu and
Yanbin Luo
International Journal of Systems Science, 2017, vol. 48, issue 2, 357-366
Abstract:
This paper considers H∞ controller design for a class of networked switched discrete systems under asynchronous switching. The sojourn probability information – the probability of the switched systems staying in each subsystem – is first used to rebuild the networked switched systems. Also, a time-varying lag, depending on both the network-induced delays and switching signals, is taken into consideration between the switching instants of the controllers and systems model. By considering both sojourn probability information and asynchronous switching, a new kind of networked switched system model is proposed, wherein a set of random variables are proposed to describe the sojourn probabilities of the subsystems. Then, stability analysis and H∞ performance analysis under asynchronous switching are derived. It should be noted that the system performance depends not only on the time-varying lag, but also on the sojourn probabilities. Finally, an example is given to illustrate the effectiveness of the proposed approach.
Date: 2017
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2016.1181226 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:48:y:2017:i:2:p:357-366
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20
DOI: 10.1080/00207721.2016.1181226
Access Statistics for this article
International Journal of Systems Science is currently edited by Visakan Kadirkamanathan
More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().