Stochastic difference inclusions: Results on recurrence and asymptotic stability in probability

Author

Teel, A.R. ; Hespanha, J. ; Subbaraman, A.

Author_Institution

Electr. & Comput. Eng. Dept., Univ. of California, Santa Barbara, Santa Barbara, CA, USA

fYear

2012

fDate

10-13 Dec. 2012

Firstpage

4051

Lastpage

4056

Abstract

Stability theory for stochastic difference inclusions is discussed. We summarize a framework for stochastic difference inclusions that has been introduced recently and for which a variety of new stability theory results have been obtained. In particular, we study recurrence and global asymptotic stability in probability. For these properties, we review new results on robustness, converse Lyapunov theorems, and Matrosov-function-based sufficient conditions. We also discuss input-to-state stability in probability. Examples are used to illustrate the framework and results.

Keywords

Lyapunov methods; asymptotic stability; discrete time systems; probability; robust control; stochastic systems; Matrosov-function-based sufficient condition; converse Lyapunov theorem; discrete-time stochastic system; global asymptotic stability; input-to-state stability; probability; recurrence; robustness; stability theory; stochastic difference inclusion framework; Asymptotic stability; Lyapunov methods; Markov processes; Random processes; Random variables; Robustness; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control (CDC), 2012 IEEE 51st Annual Conference on

Conference_Location

Maui, HI

ISSN

0743-1546

Print_ISBN

978-1-4673-2065-8

Electronic_ISBN

0743-1546

Type

conf

DOI

10.1109/CDC.2012.6425860

Filename

6425860