Automatica 48 (2012) 2569–2576
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Automatica
journal homepage: www.elsevier.com/locate/automatica
Brief paper
Stochastic input-to-state stability of switched stochastic nonlinear systems
✩
Ping Zhao
a,1
, Wei Feng
b
, Yu Kang
c
a
School of Electrical Engineering, University of Jinan, Jinan 250022, Shandong, China
b
College of Information Sciences and Engineering, Shandong Agricultural University, Taian 271018, Shandong, China
c
Department of Automation, University of Science and Technology of China, Hefei 230026, Anhui, China
a r t i c l e i n f o
Article history:
Received 30 August 2011
Received in revised form
13 March 2012
Accepted 7 May 2012
Available online 20 July 2012
Keywords:
Stochastic systems
Nonlinear systems
Switched systems
Stochastic input-to-state stability
SISS-Lyapunov function
a b s t r a c t
In this paper, global asymptotic stability in probability (GASiP) and stochastic input-to-state stability
(SISS) for nonswitched stochastic nonlinear (nSSNL) systems and switched stochastic nonlinear (SSNL)
systems are investigated. For the study of GASiP, the definition which we considered is not the usual
notion of asymptotic stability in probability (stability in probability plus attractivity in probability); it
can depict the properties of the system quantitatively. Correspondingly, based on this definition, some
sufficient conditions are provided for nSSNL systems and SSNL systems. Furthermore, the definition of
SISS is introduced and corresponding criteria are provided for nSSNL systems and SSNL systems. In the
proof of the above results, to overcome the difficulties coming with the appearance of switching and
the stochastic property at the same time, we generalize the past comparison principle and fully use the
properties of the functions which we constructed. In terms of the average dwell-time of the switching
laws, a sufficient SISS condition is obtained for SSNL systems. Finally, some examples are provided to
demonstrate the applicability of our results.
© 2012 Elsevier Ltd. All rights reserved.
1. Introduction
Since the performance of a real control system is affected more
or less by uncertainties such as unmodeled dynamics, parameter
perturbations, exogenous disturbances, measurement errors etc.,
the research on the robustness of control systems does always have
a vital status in the development of control theory and technology.
Aiming at robustness analysis of nonlinear control systems, a
new method from the point of view of input-to-state stability
(ISS), input-to-output stability (IOS) and integral input-to-state
stability (iISS) is developed and a series of fundamental results
centralizing on the theory of ISS-, and IOS-Lyapunov functions
✩
This work is supported by the Natural Science Foundation of China (60904024,
61074021, 60935001, 61174061, and 61004003), the Shandong Province Natural
Science Foundation for Distinguished Young Scholars (No. JQ201119), the Doctoral
Foundation of University of Jinan (XBS1012), the Research Supporting Foundation of
Young and Middle-Aged Scientists of Shandong Province (Grant No. BS2009DX015),
the Youth Science and Technology Innovation Foundation of Shandong Agricultural
University (Grant No. 23469 and 23649), the Anhui Provincial Natural Science
Foundation (11040606M143), the Fundamental Research Funds for the Central
Universities, and the Program for New Century Excellent Talents in University.
The material in this paper was not presented at any conference. This paper was
recommended for publication in revised form by Associate Editor Changyun Wen
under the direction of Editor Miroslav Krstic.
E-mail addresses: cse_zhaop@ujn.edu.cn (P. Zhao), fwsnakefa@126.com
(W. Feng), kangduyu@ustc.edu.cn (Y. Kang).
1
Tel.: +86 15806620986; fax: +86 0531 82765980.
are obtained by many scholars, i.e. Sontag, Wang and Lin, etc.
(Angeli, Sontag, & Wang, 2000; Liberzon, Morse, & Sontag, 2002;
Lin, Sontag, & Wang, 1995, 1996; Praly & Wang, 1996; Sontag,
1989; Sontag & Wang, 1995, 1996, 1997, 2001). The ISS idea has
also been applied in many fields, such as robotic systems (Angeli,
1999), signal processing (Angeli, 2002), tracking control (Arslan
& Basar, 2001), swarm formation (Ogren & Leonard, 2003), etc.
Concretely, for more details and applications, we can refer to
Sontag (2004) and references therein. Recently, Feng and Zhang
(2008) and Mancilla-Aguilar and Garcia (2001) applied this idea
to study the robustness of switched nonlinear (SNL) systems
of the form
˙
x(t) = f
i
(t, x(t), u(t)) (i ∈ I, where I is the index
set). Hespanha and Morse (1999) and Vu, Chatterjee, and Liverzon
(2007) applied this to the field of switching supervisory control.
The study of switched systems has also received more and more
attention (Khas’minskii, Zhu, & Yin, 2007; Yin & Zhu, 2010).
But, for the robust analysis of switched stochastic nonlinear
(SSNL) systems, the simultaneous existence of switching and the
stochastic property leads to the following two difficulties: (1) the
appearance of second order differential items when using the Itô
formula; and (2) the connection problem of each subsystem. So,
the robust analysis of this class of systems has not been done.
On the other hand, from the definition of ISS, we can find
that, if the input u = 0, an ISS system is necessarily GAS. So,
the study of GAS is very helpful to the study of ISS. Aiming to
study the asymptotic property of stochastic systems, GASiP is
introduced and has been studied by more and more scholars. In
0005-1098/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.automatica.2012.06.058