Research article
Finite-time stability and stabilization for stochastic markov jump
systems with mode-dependent time delays
$
Zhiguo Yan
a,b,c
, Yunxia Song
a
,JuH.Park
b,
n
a
School of Electrical Engineering and Automation, Qilu University of Technology, Jinan 250353, PR China
b
Department of Electrical Engineering, Yeungnam University, 280 Daehak-Ro, Kyongsan 38541, Republic of Korea
c
Key Laboratory of Pulp & Paper Science Technology of Ministry of Education of China, Qilu University of Technology, Jinan 250353, PR China
article info
Article history:
Received 16 August 2016
Received in revised form
10 December 2016
Accepted 6 January 2017
Available online 16 February 2017
Keywords:
Stochastic systems
Finite-time stability
Markovian jump systems
Time-delay
abstract
This paper is concerned with the problems of finite-time stability and stabilization for stochastic Markov
systems with mode-dependent time-delays. In order to reduce conservatism, a mode-dependent ap-
proach is utilized. Based on the derived stability conditions, state-feedback controller and observer-based
controller are designed, respectively. A new N-mode algorithm is given to obtain the maximum value of
time-delay. Finally, an example is used to show the merit of the proposed results.
& 2017 ISA. Published by Elsevier Ltd. All rights reserved.
1. Introduction
Markov jump systems have been widely studied due to their
widely practical applications in economic systems [1], power
systems [2] and so on. A great deal of results on such class of
systems have been obtained, e.g., [3–9]. And also, time-delay is
often encountered in practical process, such as communication
systems [10] and networked control systems [11,12]. Considering
the above practical phenomena, a class of more general model of
Markov jump systems with time-delays have been paid more at-
tention gradually. Many interesting results have been obtained for
this kind of systems. For example, [13] gave some sufficient con-
ditions for stochastic stability of Markov jump systems with time-
delay and partially known transition probabilities. The stability of
delayed recurrent neural networks with impulse control and
Markovian jump parameters was investigated in [14]. The litera-
ture [15] addressed
performance analysis problem for singular
Markov jump delayed systems with polyhedral parameter un-
certainties and [16] investigated delayed state feedback
stabilization of uncertain Markovian jump linear systems with
random Markov delays.
Recently, finite-time stability has also received increasing at-
tention and been found some applications in practical process,
such as, avoiding saturation or the excitation of nonlinear dy-
namics during the transient [17]. The concept of finite-time sta-
bility was first introduced in the 1950s and played an important
role in addressing transient performances of control systems.
Roughly speaking, a system is said to be finite-time stable if for a
given time-interval
T0,
, its states can not exceed a specified
bound in the time interval [18]. Many interesting results have been
obtained for this type of stability. For example, [19] investigated
the problems of finite-time stability and stabilization for Itô sto-
chastic system and [20] addressed finite-time stochastic con-
tractive bounded-ness of Markovian jump systems. The literature
[21] studied observer-based state feedback finite-time control for
nonlinear jump systems with time-delay. and [22] investigated
finite-time
control for Markovian jump systems with mode-
dependent time-varying delays.
Although several interesting results on the problems of finite-
time stability and stabilization have been reported, it has not yet
been fully investigated for Markovian jump systems with mode-
dependent time-delays. In these works, a key method is to con-
struct the following inequality [20–22]
α
[′() ()]
<[′() ()]
()
dx tPxt
dt
xtPxt,
1
i
i
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/isatrans
ISA Transactions
http://dx.doi.org/10.1016/j.isatra.2017.01.018
0019-0578/& 2017 ISA. Published by Elsevier Ltd. All rights reserved.
☆
This work was supported by 2015 Yeungnam University Research Grant, the
National Natural Science Foundation of China under Grant nos. 61403221, the Open
Foundation of Key Laboratory of Pulp and Paper Science and Technology of Ministry
of Education of China under Grant nos. KF201419, and the Young Teacher Visiting
Scholar Programs of Shandong Province.
n
Corresponding author.
E-mail addresses: yanzg500@sina.com (Z. Yan), songyx_123@163.com (Y. Song),
jessie@ynu.ac.kr (J.H. Park).
ISA Transactions 68 (2017) 141–149