Automatica 44 (2008) 2680–2685
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Automatica
journal homepage: www.elsevier.com/locate/automatica
Technical communique
New stability criteria for linear systems with interval time-varying delay
I
Xiefu Jiang
a,b
, Qing-Long Han
b,c,∗
a
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, Zhejiang, PR China
b
Centre for Intelligent and Networked Systems, Central Queensland University, Rockhampton QLD 4702, Australia
c
School of Computing Sciences, Central Queensland University, Rockhampton QLD 4702, Australia
a r t i c l e i n f o
Article history:
Received 3 January 2007
Received in revised form
14 February 2008
Accepted 21 February 2008
Available online 18 September 2008
Keywords:
Lyapunov–Krasovskii functional
Robustness
Uncertainty
Stability
Delay
Linear matrix inequality (LMI)
a b s t r a c t
This paper investigates robust stability of uncertain linear systems with interval time-varying delay.
The time-varying delay is assumed to belong to an interval and is a fast time-varying function. The
uncertainty under consideration includes polytopic-type uncertainty and linear fractional norm-bounded
uncertainty. A new Lyapunov–Krasovskii functional, which makes use of the information of both the lower
and upper bounds of the interval time-varying delay, is proposed to drive some new delay-dependent
stability criteria. In order to obtain much less conservative results, a tighter bounding for some term is
estimated. Moreover, no redundant matrix variable is introduced. Finally, three numerical examples are
given to show the effectiveness of the proposed stability criteria.
© 2008 Elsevier Ltd. All rights reserved.
1. Introduction
During the past decade, many researchers have devoted to
investigating robust stability of the system
˙
x(t) = [A + ∆A(t)]x(t) + [B + ∆B(t)]x(t − τ (t)),
x(t) = φ(t), t ∈ [−τ
M
, 0],
(1)
where x(t) ∈ R
n
is the state vector; A and B are known
parameter matrices of appropriate dimensions, ∆A(t) and ∆B(t)
are unknown real matrices of appropriate dimensions representing
the system’s time-varying parameter uncertainties; τ (t) is the
time-varying delay; and φ(t) is the initial condition.
In the time-domain, there are two approaches available for
studying robust stability of system (1): Razumikhin Theorem
approach and Lyapunov–Krasovskii functional approach. Applying
Razumikhin Theorem, one can derive a robust stability criterion
which allows a fast time-varying delay. It is well-known that
the Lyapunov–Krasovskii functional approach (Gu, 2001; Gu,
Kharitonov, & Chen, 2003; Han, 2005a; Han, Yu, & Gu, 2004) can
usually provide less conservative results than the Razumikhin
I
This paper was not presented at any IFAC meeting. This paper was
recommended for publication in revised form by Associate Editor Keqin Gu under
the direction of Editor Andre L. Tits.
∗
Corresponding author. Tel.: +61 7 4930 9270; fax: +61 7 4930 9729.
E-mail address: q.han@cqu.edu.au (Q.-L. Han).
Theorem approach since the former takes advantage of the
additional information of the delay. Therefore, in recent years,
much attention has been paid on robust stability analysis of the
system (1) by using the Lyapunov–Krasovskii functional approach.
In Han (2004), the author considered robust stability of the system
(1), where τ(t) satisfied 0 ≤ τ (t) ≤ τ
M
and ˙τ (t) ≤ τ
d
< 1.
The same problem was also studied in Fridman and Shaked (2003),
where two cases of τ (t) were considered: (1): 0 ≤ τ(t) ≤ τ
M
and
˙τ(t) ≤ τ
d
< 1; (2): 0 ≤ τ (t) ≤ τ
M
.
With the development of networked control technology,
increasing attention has been paid to the study of stability analysis
and controller design of networked control systems (NCSs) due
to their low cost, simple installation and maintenance, and high
reliability. For the NCSs, the sampling data and controller signals
are transmitted through a network. As a result, it leads to a
network-induced delay in a networked control closed-loop system.
The existence of such kind of delay in a network-based control loop
may induce instability or poor performance of NCSs. As pointed
out by Yue, Han, and Peng (2004), NCSs are typical systems with
interval time-varying delay. In fact, we consider the following
system controlled through a network
˙
x(t) = [A + ∆A(t)]x(t) + [B + ∆B(t)]u(t) (2)
where x(t) ∈ R
n
is the state vector and u(t) ∈ R
p
is the input
vector. In the presence of the control network, which is shown
in Fig. 1, data transfer between the controller and the remote
system, e.g. sensors and actuators in a distributed control system
0005-1098/$ – see front matter © 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.automatica.2008.02.020