Exponential Delay Dependent
Stabilization for Time-Varying Delay
Systems With Saturating
Actuator
Pin-Lin Liu
Associate Professor
Department of Electrical Engineering,
Chienkuo Technology University,
Changhua,
500 Taiwan, R.O.C.
This paper deals with the stabilization criteria for a class of time-
varying delay systems with saturating actuator. Based on the
Lyapunov–Krasovskii functional combining with linear matrix in-
equality techniques and Leibniz–Newton formula, delay-
dependent stabilization criteria are derived using a state feedback
controller. We also consider efficient convex optimization algo-
rithms to the time-varying delay system with saturating actuator
case: the maximal bound on the time delay such that the pre-
scribed level of operation range and imposed exponential stability
requirements are still preserved. The value of the time-delay as
well as its rate of change are taken into account in the design
method presented and further permit us to reduce the conserva-
tiveness of the approach. The results have been illustrated by
given numerical examples. These results are shown to be less
conservative than those reported in the literature.
DOI: 10.1115/1.4002713
Keywords: Leibniz–Newton formula, linear matrix inequality,
time delay, delay-dependence
1 Introduction
Both time-delay and saturating controls are commonly encoun-
tered in various engineering systems and are frequently a source
of instability. Stability analysis and synthesis of time-delay sys-
tems are important issues addressed by many authors, and some
mature methods have been widely used to deal with these prob-
lems 1–22. Many methods to check the stability of time-delay
systems 1,7,8,13,16,22or linear systems with saturating controls
have been proposed 2–6,9–12,15,17–21.Nonlinear systems with
time-delay constitute basic mathematical models of real phenom-
ena, for instance, in circuits theory, economics, and mechanics.
Not only dynamical systems with time-delay are common in
chemical processes and long transmission lines in pneumatic, hy-
draulic, or rolling mill systems, but computer controlled systems
requiring numerical computation also have time delays in control
loops. The presence of time delays in control loops usually de-
grades system performance and complicates the analysis and de-
sign of feedback controllers. Actuator saturation and time delays
are often observed together in control systems. To deal with both
problems effectively, appropriate design methods are required. Up
to now, only a few methods were reported to deal with these
problems simultaneously. Cao et al. 2considered the design of
the antiwindup gain for further enlargement of the closed-loop
stability region. Unlike in the design of feedback gain by Hu et al.
6, the design of antiwindup gain by Cao et al. 2cannot be
formulated into a linear matrix inequality LMIoptimization
problem. Chen and Wang 3studied the stabilization problem of
saturating a time-delay system with state feedback and sampled-
state feedback and they derived several sufficient conditions to
ensure the system stability in terms of norm inequalities. Chou et
al. 4exploited a sufficient condition to stabilize a linear uncer-
tain time delay system containing input saturation. The problem of
robust stabilization of uncertain time delay systems containing a
saturating actuator was addressed by Niculescu et al. 14by a
high gain approach. Oucheriah 15considered a method to syn-
thesize a globally stabilizing state feedback controller by means of
an asymptotic observer for time-delay systems. In Ref. 18,a
dynamic antiwindup method was presented for the systems with
input delay and saturation. In Ref. 13, a LMI-based approach is
proposed to analyze the stability and domain of attraction for sys-
tems with exponential stability.
Recently, increasing attention has been paid to the study of the
stability of systems with both time-delay and saturating actuator
because of its practical usefulness 2–6,9–12,15,17–20. The sta-
bility problem of time-delay systems with a saturating actuator
has been proposed that are based on the matrix norm or matrix
measure 3–5,9–12,14,17,18,21. Unfortunately, matrix norm and
matrix measure operations usually render the criteria more con-
servative. Therefore, recently, a new stability criterion based on
the LMI techniques was proposed 2,19,20. However, the stabil-
ity analyses of the operators are still based on matrix norm ma-
nipulations, which may lead to conservative results. Considering a
Lyapunov–Krasovskii functional, a synthesis technique based
upon LMIs was used to determine simultaneously a robust stabi-
lizing state feedback and a set of admissible conditions from
which the resulting trajectories are asymptotically stable when the
saturation effectively occurs. This work concerns both the design
of stabilizing controllers and the determination of the associated
domains of safe initial conditions for linear systems with state
delay and saturating controls. The method used is based on the
Lyapunov–Krasovskii approach 2,19. The synthesis of both a
suitable gain matrix and an associated set of initial conditions is
carried out by LMIs 1. A convex optimization problem is then
proposed in order to maximize the size of the set of admissible
initial conditions 13. However, in the control of a time-varying
delay system with saturating actuator, it is usually desirable to
design a controller, which not only robustly stabilizes the system
but also estimates the bound of delay time hto keep the stabil-
ilization of the system. Furthermore, the results are somewhat
conservative, especially in situations where delays are small; there
is room for investigation.
This paper deals with the robust stabilization criteria for a class
of time-varying delay systems with a saturating actuator. Based on
the Lyapunov–Krasovskii functional combining with LMI tech-
niques and the Leibniz–Newton formula, delay-dependent stabili-
zation criteria are derived using a state feedback controller. We
also consider an optimization particular to the time-varying delay
system with a saturating actuator case: the maximal bound on the
time delay such that the prescribed level of operation range and
imposed exponential stability requirements are still preserved. The
designed controller is dependent on the time delay and its rate of
change. From the illustrated examples, if the delay time lengthens,
the decay rate becomes conservative. We claim that the sharpness
of the upper bound delay time hvaries with the chosen decay rate
. The results have been illustrated by the given numerical ex-
amples. These results are shown to be less conservative than those
reported in the literature.
2 Main Result
Consider the following time-varying delay systems with a satu-
rating actuator described by
x
˙t=A0xt+A1xtht兲兲 +Bsatut兲兲 共1a
Contributed by the Dynamic Systems Division of ASME for publication in the
JOURNAL OF DYNAMIC SYSTEMS,MEASUREMENT,AND CONTROL. Manuscript received
April 13, 2009; final manuscript received February 23, 2010; published online
November 23, 2010. Assoc. Editor: Guoming George Zhu.
Journal of Dynamic Systems, Measurement, and Control JANUARY 2011, Vol. 133 / 014502-1
Copyright © 2011 by ASME
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xt=
t,th,0兴共1b
where xtRnis the state vector, utRmis the control input
vector, and xtis the state at time tdenoted by xtsªxt+s.A0,
A1, and Bare known constant matrices with appropriate dimen-
sions.
tis a smooth vector-valued initial function.
Time-delay htis a time-varying continuous function that sat-
isfies
0hth,h
˙thd12
where hand hdare constants.
The saturating function is defined as follows:
satut兲兲 =satu1t,satu2t兲兲, ...,satumt兲兲兴T3
The operation of satuit兲兲 is linear for −UiuiUias
satuit兲兲 =
Uiif uiUi0
uiif UiuiUi
Uiif uiUi0
4
Throughout this paper, we will use the following concept of
stabilization for the time delay system with a saturating actuator
Eq. 1兲兲.
DEFINITION 1. The time-varying delay system with a saturating
actuator (Eq. 1) is said to be stable in closed-loop via memory-
less state feedback control law if there exists a control law ut
=Kxt,KRmxn such that the trivial solution xt兲⬵0of the
functional differential equation associated to the closed-loop sys-
tem is uniformly asymptotically stable.
In order to develop our result by considering a state feedback
control law ut=Kxt, the saturating term satKxt兲兲 can be writ-
ten in an equivalent form
satKxt兲兲 =D
x兲兲Kxt,D
x兲兲 Rmxn 5
where D
x兲兲 is a diagonal matrix for which the diagonal ele-
ments
ixsatisfy for i=1,2,...,m,
ix=
Ui
Kxi
if KxiUi0
1if UiKxiUi
Ui
Kxi
if KxiUi0
6
and therefore,
0
ix17
From Eqs. 1a,1b, and 37, we can rewrite the time-
varying delay system with saturating actuator as follows:
x
˙t=AFxt+A1xtht兲兲 共8
where AF=A0+BD
x兲兲K.
For the above system Eq. 8兲兲, the main objective is to find the
range of hand guarantee the stabilization for the time-varying
delay system with a saturating actuator Eq. 8兲兲. When the time
delay is unknown, how long can time delay be tolerated to keep
the system stable? To do this, two fundamental lemmas are re-
viewed.
LEMMA 1 13.If there exist symmetric positive-definite matrix
X33 0and arbitrary matrices X11 ,X
12 ,X
13 ,X
22 , and X23 such
that
X=
X11 X12 X13
X12
TX22 X23
X13
TX23
TX33
09
then we obtain
tht
t
x
˙TsX33x
˙sds
tht
t
xTtxTtht兲兲 x
˙Ts
X11 X12 X13
X12
TX22 X23
X13
TX23
T0
xt
xtht兲兲
x
˙s
ds
10
LEMMA 2 1.The following matrix inequality
QxSx
STxRx
011
where Qx=QTx,Rx=RTx, and Sxdepend on affine on x
is equivalent to
Rx012a
Qx012b
QxSxR−1xSTx012c
The nominal unforced time-varying delay saturating actuator
system Eq. 1兲兲 can be written as
x
˙t=A0xt+A1xtht兲兲 共13
Now, we describe our method for determining the stabilization
of time-varying delay systems Eq. 13兲兲 in the following theo-
rem.
THEOREM 1.Given the scalars h0and hd0, the nominal
unforced time-varying delay system (Eq. (13)) is asymptotically
stable if there exist symmetric positive-definite matrices P 0,
Q0,R0, and X0and a semipositive-definite matrix
X=
X11 X12 X13
X12
TX22 X23
X13
TX23
TX33
0
such that the following LMIs hold:
=
11 12 13
12
T22 23
13
T23
T33
014a
RX33 014b
where
11 =A0
TP+PA0+Q+1−hd兲共X13 +X13
T+hX11
12 =PA1+1−hd兲共X13 +X23
T+hX12
13 =hA0
TR
23 =hA1
TR
22 =1−hd兲共QX23 X23
T+hX22
33 =−hR
Proof. Select the following Lyapunov–Krasovskii functional to
be
Vxt=xTtPxt+
tht
t
xTsQxsds
+
ht
0
t+
t
x
˙TsRx
˙sdsd
15
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Calculating the derivative of Eq. 15with respect to talong the
trajectory of the nominal unforced time-varying delay system Eq.
13兲兲 yields
V
˙xt=xTt兲共A0
TP+PA0xt+xTtPA1xtht兲兲 +xTt
ht兲兲A1
TPxt+xTtQxtxTtht兲兲共1−h
˙t兲兲Qxt
ht兲兲 +x
˙TthRx
˙t1−h
˙t兲兲
th
t
x
˙TsRx
˙sds =xTt
A0
TP+PA0+Qxt+xTtPA1xtht兲兲 +xTt
ht兲兲A1
TPxtxTtht兲兲共1−hdQxtht兲兲
+x
˙TthRx
˙t+1−hd
tht
t
x
˙Ts兲共X33 Rx
˙sds 1
hd
tht
t
x
˙TsX33x
˙sds 16
Using the Leibniz–Newton formula xtxtht兲兲
=tht
tx
˙sds and Lemma 1, we obtain
1−hd
tht
t
x
˙TsX33x
˙sds 1−hd
tht
t
xTtxTtht兲兲 x
˙Ts
X11 X12 X13
X12
TX22 X23
X13
TX23
T0
xt
xtht兲兲
x
˙s
ds 1−hd
xTthX11xt+xTthX12xtht兲兲 +xTtX13
tht
t
x
˙sds +xTtht兲兲hX12
Txt+xT共共t
ht兲兲hX22xtht兲兲+xTtht兲兲X23
tht
t
x
˙sds +
tht
t
x
˙TsdsX13
Txt+
tht
t
x
˙TsdsX23
Txt
ht兲兲
=1−hd兲兵xTthX11xt+xTthX12xtht兲兲 +xTtX13xtxtht兲兲兴 +xTt
ht兲兲hX12
Txt+xTtht兲兲hX22xtht兲兲 +xTtht兲兲X23xtxtht兲兲兴 +xtxt
ht兲兲兴TX13
Txt+xtxtht兲兲兴TX23
Txtht兲兲其 =1−hd兲兵xTthX11xt+xTthX12xtht兲兲
+xTtX13xtxTtht兲兲X13
Txt+xTtht兲兲hX12
Txt+xTtht兲兲hX22xtht兲兲 +xTt
ht兲兲X23xtxTtht兲兲X23xtht兲兲 +xTtX13
TxtxTtX13
Txtht兲兲 +xTtX23
Txtht兲兲
xTtht兲兲X23
Txtht兲兲其 =1−hd兲兵xTt兲关hX11 +X13
T+X13xt+xTt兲关hX12 X13 +X23
Txt
ht兲兲 +xTtht兲兲关hX12
TX13
T+X23xt+xTth兲关hX22 X23 X23
Txtht兲兲其 共17
Substituting the above Eq. 17into Eq. 16yields the follow-
ing equation:
V
˙xt
Tt
t1−hd
tht
t
x
˙Ts兲共RX33x
˙sds
18
where
Tt=xTtxTtht兲兲
and
=
11 12
12
T22
with
11 =A0
TP+PA0+Q+1−hd兲共X13 +X13
T+hX11+hA0
TRA0
12 =PA1+1−hd兲共X13
T+X23 +hX12+hA0
TRA1
22 =1−hd兲共QX23 X23
T+hX22+hA1
TRA1
Finally, using the Schur complements of Lemma 2, with some
effort we can show that Eq. 18guarantees V
˙xt0. Condition
14of the present Theorem 1 is satisfied if V
˙xt0, then
0 and RX33 0, if and only if Eq. 14holds. Therefore, the
nominal unforced time-varying delay system Eq. 13兲兲 is asymp-
totically stable. This completes the proof.
According to Theorem 1, we describe our method for determin-
ing the stabilization of the time-varying delay system with a satu-
rating actuator Eq. 1兲兲. The main aim of this paper is to develop
delay-dependent conditions for the stabilization of the time-
varying delay saturating actuator system Eq. 1兲兲 under the state
feedback control law ut=Kxt. More specifically, our objective
is to determine bounds for the delay time by using the Lyapunov–-
Krasovskii functional and LMI methods with the Leibniz–Newton
formula. Theorem 2 gives an LMI-based computational procedure
to determine the state feedback controller. Then, we have the fol-
lowing result.
THEOREM 2.Given the scalars h0and hd0, the time-
varying delay saturating actuator system (Eq. 1) is asymptoti-
cally stabilizable via the memoryless state feedback controller if
there exist symmetric positive-definite matrices W0,U0,
and Z0, a semipositive-definite matrix
T=
T11 T12 T13
T12
TT22 T23
T13
TT23
TT33
0
and a matrix Y with appropriate dimensions such that the follow-
ing holds:
Journal of Dynamic Systems, Measurement, and Control JANUARY 2011, Vol. 133 / 014502-3
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=
11 12 13
12
T22 23
13
T23
T33
019a
WT33 019b
where
11 =WA0
T+A0W+BD
x兲兲Y+YTDT
x兲兲BT+U+1−hd
T13 +T13
T+hT11
12 =A1W+1−hd兲共T13 +T23
T+hT12
13 =hWA0
T+YTDT
x兲兲BT
22 =1−hd兲共UT23 T23
T+hT22
23 =hWA1
T
33 =−hZ
Then, the time-varying delay system with a saturating actuator
Eq. 1兲兲 is asymptotically stable for with allowable time delay h
under the state feedback control law and K=YW−1 is a stabilizing
gain.
Proof. In view of Theorem 1, to prove the asymptotic stability
of the closed-loop system with control ut=Kxt, it suffices to
show that there exist symmetric, positive-definite matrices P0,
Q0, R0, and X0 such that Eq. 14remains valid with A0
replaced by A0+BD
x兲兲K. Pre- and post-multiplying both sides
of Eq. 14by diagP−1 ,P−1 ,R−1and letting W=P−1,K=YW−1,
P−1QP−1 =U,P−1XijP−1 =Tij i,j=1,2,3,Z=R−1, and
R−1 P−1R
X33 P−1 =WT33 lead to Eq. 18. Thus, if W,U,Z,Y,
and Tij are a set of feasible solutions to LMI Eq. 19兲兲, then W
=P−1,P−1QP−1 =U,P−1XijP−1 =Tij, and Y=KW−1, satisfying Eq.
19with A0replaced by A0+BD
x兲兲K. This completes our
proof.
3 Extension to Exponential Stability for Time Delay
Saturating Actuator Systems
Consider that the time-varying delay system with a saturating
actuator Eq. 1兲兲 utilizes the following transformation:
zt=e
txt兲共20
where
0 is stability degree delay decay rateto transform Eq.
1into
z
˙t=A
zt+A1
ztht兲兲 共21
where A
=A0+BD
x兲兲K+
Iand A1
=A1e
h.
By applying Theorem 2 to system 21, we can immediately
have Theorem 3.
THEOREM 3.Given scalars h0and hd0, the time-varying
delay saturating actuator system (Eq. (21)) is exponentially stable
with decay rate
via the memoryless state feedback controller if
there exist symmetric positive-definite matrices W0,U0,Z
0, a semipositive-definite matrix
T=
T11 T12 T13
T12
TT22 T23
T13
TT23
TT33
0
and a matrix Y with appropriate dimensions such that the follow-
ing LMIs hold:
=
11 12 13
12
T22 23
13
T23
T33
022a
WT33 022b
where
11 =WA0+
IT+A0+
IW+BD
x兲兲Y+YTDT
x兲兲BT
+U+1−hd兲共T13 +T13
T+hT11
12 =A1e
hW+1−hd兲共T13 +T23
T+hT12
13 =hWA0+
IT+YTDT
x兲兲BT
22 =1−hd兲共UT23 T23
T+hT22
23 =hWA1
Te
h
33 =−hZ
Then, the time delay system Eq. 21兲兲 is exponentially stable
for with allowable time delay hunder the state feedback control
law and K=YW−1 is a stabilizing gain.
Proof. Replace A0and A1with A0+BD
x兲兲K+
Iand A1e
h,
respectively, in Theorem 2 and let K=YW−1 then the proof of
Theorem 3 follows from Theorem 2.
Remark 1. As in the stabilization problem, the upper bound h,
which ensures that time-delays Eq. 1兲兲 is stabilizable for any h,
can be determined by solving the following quasi-convex optimi-
zation problem when the other bound of time delay his known:
maximize h
subject to Eq. 19or22:W0, U0,
Z0, and T023
Inequality 23is a quasi-convex optimization problem and can
be obtained efficiently using MATLAB LMI Toolbox. Then, the
controller K=YW−1 stabilizes system 1.
To show the usefulness of our result, let us consider the follow-
ing numerical examples.
4 Examples
In this section, two numerical examples are presented to com-
pare with the proposed stabilization method with previous results.
Example 1. Consider the time-varying delay system with an
actuator saturated at level 1 described as follows:
x
˙t=A0xt+A1xtht兲兲 +Bsatut兲兲 共24
where
A0=
−4 0
1−5
,A1=
−1 1
0−1
,B=
10
01
Assume that the operation range
ixis inside the sector 0.5,
1. The problem is to design a state feedback controller to estimate
the delay time hsuch that the above system is to be asymptoti-
cally stable.
Solution. Here, we want to find a state feedback controller that
asymptotically stabilizes a class of time delay systems with a satu-
rating actuator. First, apply the same state feedback controller 11
as hd=0 and
K=
− 0.1023 − 0.0168
− 0.0168 − 0.0855
We check the feasibility of LMIs Eq. 19兲兲, and we can find that
the LMIs are feasible and obtain the solutions of the inequalities
W=
4.9680 0.7689
0.7689 4.0779
,U=
16.3152 0.0344
0.0344 16.1438
,
Z=
79.1165 0.7696
0.7696 78.1970
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T11 =
5.5236 0.0692
0.0692 5.4325
,T12 =
− 5.0487 − 0.0687
− 0.0687 − 4.9472
,
T13 =
− 12.8052 − 0.0997
− 0.0997 − 12.7109
T22 =
6.8806 0.1257
0.1257 6.7435
,T23 =
12.3777 0.0863
0.0863 12.2943
,
T33 =
53.1382 0.4699
0.4699 52.6460
h3.8799
An upper bound given by Liu and Su 11is h0.405. Hence,
for this example, the robust stability criterion of this paper is less
conservative than the existing result of Liu and Su 11. The simu-
lation of the above closed system for h=3.8 is depicted in Fig. 1.
On the other hand, for the case of hd=0.9, solving the following
quasi-convex optimization problem Eq. 24兲兲, the maximum up-
per bound hfor which the system is stabilized by the correspond-
ing state feedback,
K=YW−1 =
− 8.2040 15.9474
6.4402 − 17.8635
and h1.9978.
Furthermore, using the LMI Toolbox in MATLAB with an accu-
racy of 0.01by taking
K=
− 8.2040 15.9474
6.4402 − 17.8635
and 0
ix1, the variations of
ixin bound of delay time h
are shown in Table 1. As Table 1 indicates, the delay time in-
creases when the parameter
ixdecreases from 0.9 to 0.1. For
reasons mentioned above, if the operation range lengthens, the
delay time becomes less conservative. We claim that the sharpness
of the upper bound delay time hvaries with the chosen operation
range of
ix.
Remark 2. The operational range of the saturation nonlinearity
is inside the sector
ix,1,0
ix1 in actual system and
the results can be improved considerably.
Example 2. Consider the time-varying delay system with an
actuator saturated at level 1 of the form
x
˙t=A0xt+A1xtht兲兲 +Bsatut兲兲 共25
where
A0=
−2 0
1−3
,A1=
−1 0
− 0.8 − 1
,B=
12
−1 4
The problem is to design a state feedback controller to estimate
the delay time hsuch that the system Eq. 25兲兲 is to be asymp-
totically stable.
Solution. First, apply the same memoryless state feedback con-
troller 17as K=0.0212 0.0272
−0.0323 0.1060 . We calculate that the solutions
of the LMIs given in Eq. 19are feasible and h4.3949. An
upper bound given by Refs. 14,17are h0.3819 and h
0.6153, respectively. Hence, for this example, the robust stabil-
ity criterion of this paper is less conservative than the existing
results of Refs. 14,17.
Next, when
ix=0.5, hd=0.1, and
=0, solving the following
quasi-convex optimization problem Eq. 24兲兲, the maximum up-
per bound is hfor which the system is h7.6244. Therefore, we
can get the stabilizing state feedback controller for the system
Eq. 25兲兲, which is
Table 1 Bound of delay time hfor various parameters
ix
ix0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1
h2.0599 2.0371 2.0351 2.0065 1.9978 1.9905 1.9501 1.9203 1.8271
Table 2 Bound of delay time hfor various decay rates
and the change in time-varying delay hdsaturated range
ix=0.1
hd
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
0.1 7.3955 5.5316 5.3654 5.3414 5.0014 4.9821 3.5921 3.4995 3.0011
0.2 5.3596 5.3199 5.0165 4.9901 4.5991 4.3331 3.0111 2.6005 2.3534
0.3 5.3479 5.2500 4.8567 4.8167 3.5011 3.3219 2.9929 2.5401 2.3337
0.4 5.3169 5.1119 4.0119 3.1564 3.0449 3.0228 2.9001 2.1111 1.8511
0.5 5.2599 3.9510 3.2110 3.1101 2.9868 2.6878 2.6799 1.8660 1.6896
0.6 5.2452 3.6099 3.1011 3.0425 2.1300 1.8801 1.8709 1.5706 1.4796
0.7 5.2300 3.1330 2.6010 2.5010 2.0563 1.8521 1.8455 1.5499 1.5354
0.8 3.5644 3.0900 2.5401 2.4203 2.0401 1.8411 1.8391 1.7001 1.6001
0.9 3.5191 3.0631 2.4999 2.2010 2.0005 1.8205 1.8101 1.6201 1.5347
Fig. 1 The simulation of the example 1 for h=3.8 sec
Journal of Dynamic Systems, Measurement, and Control JANUARY 2011, Vol. 133 / 014502-5
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