Joint stochastic distribution tracking control for multivariate descriptor systems with non-gaussian variables

Liping Yin and Lei Guo

International Journal of Systems Science, 2011, vol. 43, issue 1, 192-200

Abstract: This article considers a new tracking control problem for a class of nonlinear stochastic descriptor systems where the tracked target is a given joint probability density function (JPDF). The controlled plants can be represented by multivariate discrete-time descriptor systems with non-Gaussian disturbances and nonlinear output equations. The control objective is to find crisp algorithms such that the conditional output JPDFs can follow the given target JPDF. A direct relationship is established between the JPDFs of the transformed tracking error and the stochastic input. An optimisation approach is presented such that the distances between the output JPDF and the desired one are minimised. Furthermore, a stabilisation suboptimal control strategy is proposed using the linear matrix inequality-based Lyapunov theory. Finally, simulations are provided to demonstrate the effectiveness of the stochastic tracking control algorithms.

Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2010.488754 (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:43:y:2011:i:1:p:192-200

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

DOI: 10.1080/00207721.2010.488754

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 ().