Observer-based dissipative control for Markovian jump systems via delta operators

R. Sakthivel, M. Rathika, Srimanta Santra and M. Muslim

International Journal of Systems Science, 2017, vol. 48, issue 2, 247-256

Abstract: This paper addresses the issue of observer-based dissipative control problem for a class of Markovian jump systems with random delay via delta operator approach. First, based on the construction of a novel Lyapunov functional together with the use of free-weighting matrix approach, a new set of sufficient conditions is established which ensures the stochastic asymptotic stability and dissipativity of the closed-loop augmented Markovian jump delta operator system. Next, the result is extended to design an observer-based state feedback dissipative control law such that the resulting closed-loop system is stochastically asymptotically stable with the desired dissipative performance index. Further, the existence of control laws is formulated in the form of linear matrix inequalities (LMIs) which can be easily solved by using some standard numerical packages. Also, the observer and control gains can be calculated by using the solutions of an obtained set of LMIs. It is worth pointing out that the dissipative control problem considered here includes the H∞ and passivity-based control problems as special cases. Finally, two numerical examples with simulation are presented to demonstrate the effectiveness of the obtained design technique.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2016.1177131 (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:247-256

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2016.1177131

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 ().