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Volume 2009, Article ID 240707, 13 pagesdoi:10.1155/2009/240707 Research Article Stabilization of Discrete-Time Control Systems with Multiple State Delays Medina Rigoberto Departamento d

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Volume 2009, Article ID 240707, 13 pages

doi:10.1155/2009/240707

Research Article

Stabilization of Discrete-Time Control Systems

with Multiple State Delays

Medina Rigoberto

Departamento de Ciencias Exactas, Universidad de Los Lagos, Casilla 933, Osorno, Chile

Correspondence should be addressed to Medina Rigoberto,rmedina@ulagos.cl

Received 16 March 2009; Accepted 21 June 2009

Recommended by Leonid Shaikhet

We give sufficient conditions for the exponential stabilizability of a class of perturbed time-varying difference equations with multiple delays and slowly varying coefficients Under appropiate growth conditions on the perturbations, combined with the “freezing” technique, we establish explicit conditions for global feedback exponential stabilizability

Copyrightq 2009 Medina Rigoberto This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

1 Introduction

Let us consider a discrete-time control system described by the following equation in C n:

x k  1  Akxk  A1kxk − r  Bkuk, 1.1

where C n denotes the n-dimensional space of complex column vectors, r ≥ 1 is a given

integer, x : Z → C n is the state, u : Z → C m m ≤ n is the input, Z is the set of nonnegative integers Hence forward,·   · C n is the Euclidean norm; A and B are variable matrices of compatible dimensions, A1is a variable n × n-matrix such that

sup

and ϕ is a given vector-valued function, that is, ϕk ∈ C n

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The stabilizability question consists on finding a feedback control law uk  Lkxk,

for keeping the closed-loop system

x k  1  Ak  BkLk xk  A1kxk − r, 1.4

asymptotically stable in the Lyapunov sense

The stabilization of control systems is one of the most important properties of the systems and has been studied widely by many reseachers in control theory;see, e.g., 1

11  and the references therein It is recognized that the Lyapunov function method serves

as a main technique to reduce a given complicated system into a relatively simpler system and provides useful applications to control theory, but finding Lyapunov functions is still a difficult task see, e.g., 1 3,12,13  By contrast, many methods different from Lyapunov functions have been successfully applied to establish stabilizability results for discrete-time equations For example, to the linear system

if the evolution operatorΦk, s generated by Ak is stable, then the delay control system

1.1-1.2 is asymptotically stabilizable under appropiate conditions on A1k see 4,8,14  For infinite-dimensional control systems, the study of stabilizabilization is more complicated and requires sophisticated techniques from semigroup theory

The concept of stabilizability has been developed and successfully applied in different settings see, e.g., 9, 15, 16  For example, finite- and infinite-dimensional discrete-time control systems have been studied extensivelysee, e.g., 2,5,6,10,17–20 

The stabilizability conditions obtained in this paper are derived by using the

“freezing” technique see, e.g., 21–23  for perturbed systems of difference equations with slowly varying coefficients and do not involve either Lyapunov functions or stability assumptions on the associated evolution operatorΦk, s With more precision, the freezing technique can be described as follows If m ∈ Zis any fixed integer, then we can think of the autonomous system

as a particular case of the system1.1, with its time dependence “frozen” at time m Thus, in

this paper it is shown that if each frozen system is exponentially stabilizable and the rate of change of the coefficients of system 1.1 is small enough, then the nonautonomous system

1.1-1.2 is indeed exponentially stabilizable

The purpose of this paper is to establish sufficient conditions for the global exponential feedback stabilizability of perturbed control systems with both varying and time-delayed states

Our main contributions are as follows By applying the “freezing” technique to the control system 1.1-1.2, we derive explicit stabilizability conditions, provided that the coefficients are slowly varying Applications of the main results to control systems with many delays and nonlinear perturbations will also be established in this paper This technique will allow us to avoid constructing the Lyapunov functions in some situations For instance, it

is worth noting that Niamsup and Phat 2 established sufficient stabilizability conditions

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for the zero solution of a discrete-time control system with many delays, under exponential growth assumptions on the corresponding transition matrix By contrast, our approach does not involve any stability assumption on the transition matrix

The paper is organized as follows In Section 2 we introduce notations, definition, and some preliminary results InSection 3, we give new sufficient conditions for the global exponential stabilizability of discrete-time systems with time-delayed states Finally, as an application, we consider the global stabilization of the nonlinear control systems

2 Preliminaries

In this paper we will use the following control law:

where Lk is a variable m × n-matrix.

To formulate our results, let us introduce the following notation Let A be a constant

n × n matrix and let λ j A, j  1, 2, , n, denote the eigenvalues of A, including their

multiplicities Put

g A 

⎣N2A −n

j1

λ j A2

1/2

where NA is the Hilbert-Schmidt Frobenius norm of A; that is, N2A  TraceAA.

The following relation

g A ≤

 1

is true, and will be useful to obtain some estimates in this work

Theorem A 17,Theorem 3.7  For any n × n-matrix A, the inequality

A m ≤m1

j0

m!

ρ A m −j

g A j

m − j !

holds for every nonnegative integer m, where ρ A is the spectral radius of A, and m1 min{m, n −

1}

Remark 2.1 In general, the problem of obtaining a precise estimate for the norm of

matrix-valued and operator-matrix-valued functions has been regularly discussed in the literature, for example, see Gel’fond and Shilov24 and Daleckii and Krein 25

The following concepts of stability will be used in formulating the main results of the papersee, e.g., 26 

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Definition 2.2 The zero solution of system1.4–1.2 is stable if for every ε > 0 and every

k0∈ Z, there is a number δ > 0 depending on ε and k0 such that every solution xk of the

system withϕk < δ for all r − k0, r − k0 1, , k0, satisfies the condition

Definition 2.3 The zero solution of1.4 is globally exponentially stable if there are constants

M > 0 and c0∈ 0, 1 such that

xk ≤ Mc k

0max

−r≤s≤0 ϕ s , k ∈ Z 2.6

for any solution xk of 1.4 with the initial conditions 1.2

Definition 2.4 The pair Ak, Bk is said to be stabilizable for each k ∈ Z if there is a

matrix Lk such that all the eigenvalues of the matrix C L k  Ak  BkLk are located inside the unit disk for every fixed k ∈ Z Namely,

ρ L sup

Remark 2.5 The control u k  Lkxk is a feedback control of the system.

Definition 2.6 System1.1 is said to be globally exponentially stabilizable at x  0 by means

of the feedback law2.1 if there is a variable matrix Lk such that the zero solution of 1.4

is globally exponentially stable

3 Main Results

Now, we are ready to establish the main results of the paper, which will be valid for the system1.1-1.2 with slowly varying coefficients

Consider in C nthe equation

subject to the initial conditions1.2, where r ≥ 1 is a given integer and Tk is a variable

n × n-matrix.

Proposition 3.1 Suppose that

a p  sup k≥0A1k < ∞,

b there is a constant q > 0 such that

T k − T

c S0: S0T·, A1·  ∞k0qk  psup l 0,1, T k l < 1.

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Then the zero solution of system3.1–1.2 is globally exponentially stable Moreover, any

solution of 3.1 satisfies the inequality

xk ≤ β0 ϕ0  γ

1− S0

where

β0 sup

l,k 0,1,

T k l < ∞, γ  p max

−r≤k≤0 ϕ k ∞

k0

sup

l 0,1,

T k l 3.4

Proof Rewrite3.1 in the form

x k  1 − Tsxk  Tk − Tsxk  A1kxk − r, 3.5

with a fixed nonnegative integer s The variation of constants formula yields

x m  1  T m1sϕ0 m

j0

T m −j s T

j − Ts x

j  A1

j x

j − r 3.6

Taking s  m, we have

x m  1  T m1mϕ0 m

j0

T m −j m T

j − Tm x

j  A1

j x

Hence,

xm  1 ≤ β0 ϕ0 m

j0

T m −j m qm − j x

j x

j − r

≤ β0 ϕ0  qmax

0≤k≤mxkm

k0

T k m k m

k0

T k m max

−r≤j≤k x

j 1k

≤ β0 ϕ0  max

0≤k≤mxk∞

k0

qk  p sup

l 0,1,

T k l  γ.

3.8 Thus,

xm  1 ≤ β0 ϕ0  γ  max

0≤j≤m x

j



k0

qk  p sup

l 0,1,

T k l 3.9

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max 0≤k≤m1xk ≤ β0 ϕ0  γ  S0 max

From this inequality we obtain

max 0≤k≤m1xk ≤ β0 ϕ0  γ

But, the right-hand side of this inequality does not depend on m Thus, it follows that

xk ≤ β0 ϕ0  γ

1− S0

This proves the global stability of the zero solution of3.1–1.2

To establish the global exponential stability of3.1–1.2, we take the function

with α > 0 small enough, where xk is a solution of 3.1

Substituting3.13 in 3.1, we obtain

x α k  1  Tkx α k   A1kx α k − r, 3.14 where

T k  e α T  k , A1 k  e r1α A1 k 3.15

Applying the above reasoning to3.14, according to inequality 3.3, it follows that x α k is

a bounded function Consequently, relation3.13 implies the global exponential stability of the zero solution of system3.1–1.2

Computing the quantities β0and S0, defined by

β0 sup

k,l 0,1,

T k l ,

S0∞

k0

kq  p sup

l 0,1,

is not an easy task However, in this section we will improve the estimates to these formulae

Proposition 3.2 Assume that (a) and (b) hold, and in addition

v0 sup

k≥0

g Tk < ∞, ρ0 sup

k≥0

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where ρ Tk is the spectral radius of Tk for each k ∈ Z If

S0n−1

k0

v k

0

k!



k  1q

1− ρ0 k2 p

1− ρ0 k1



< 1, 3.18

then the zero solution of system3.1–1.2 is globally exponentially stable.

Proof Let us turn now to inequality3.3 Firstly we will prove the inequality



k0

kq  p sup

l 0,1,

T k l ≤ qλ

where

λ0n−1

k0

k  1v k

0

k!

1− ρ0 k2, λ1n−1

k0

v k

0

k!

Consider

θ0∞

k1

k sup

l 0,1,

By Theorem A, we have

θ0≤∞

k1

n−1



j0

kk!ρ k0−j v0j

k − j !

But



k1

kk!z k −j

k − j ! ≤∞

k0

k  1z k −j

k − j !  d j1

dz j1



k0

z k1



 d j1

dz j1z 1 − z−1 j 1 !1 − z−j−2 , 0 < z < 1.

3.23

Hence,

θ0≤n−1

j0

v0j

j! 3/2



k0

kk!ρ k0−j

k − j ! n−1

j0

j 1 v j0



j!

Proceeding in a similar way, we obtain



k0

sup

l 0,1,

T k l ≤ λ

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These relations yield inequality3.19 Consequently,

xk ≤ 1− qλ0− pλ1 −1

where

M0 sup

k≥1

⎝n−1

j0

k!ρ k0−j v0j

k − j !

j! 3/2

Relation 3.26 proves the global stability of the zero solution of system 3.1–1.2 Establishing the exponential stability of this equation is enough to apply the same arguments

of theProposition 3.1

Theorem 3.3 Under the assumption (a), let Ak, Bk be stabilizable for each fixed k ∈ Zwith respect to a matrix function L k, satisfying the following conditions:

i ρ L supk≥0ρ C L k < 1,

ii q L supk≥0C L k  1 − C L k < ∞, and

iii v L supk≥0g C L k < ∞.

If,

S C L , A1 n−1

k0

v L k

k!



k  1q L

1− ρ L k2 p

1− ρ L k1



< 1, 3.28

then system1.1-1.2 is globally exponentially stabilizable by means of the feedback law 2.1.

Proof Rewrite1.4 in the form

where T k  Ak  BkLk.

According to i, ii, and iii, the conditions b and 3.17 hold Furthermore, condition 3.28 assures the existence of a matrix function Lk such that condition 3.18

is fulfilled Thus, fromProposition 3.2, the result follows

Put

σ A·, B·; A1· ≡ min

where the minimum is taken over all m × n matrices Lk satisfying i, ii, and iii.

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Corollary 3.4 Suppose that (a) holds, and the pair Ak, Bk is stabilizable for each fixed k ∈ Z If

then the system1.1-1.2 is globally exponentially stabilizable by means of the feedback law 2.1.

Now, consider in C n the discrete-time control system

subject to the same initial conditions1.2, where A and B are constant matrices In addition, one

assumes that the pair A, B is stabilizable, that is, there is a constant matrix L such that all the

eigenvalues of C L  A  BL are located inside the unit disk Hence, ρC L  < 1 In this case, q L  0

and v L  gC L  Thus,

S C L , A1  p n−1

k0

g A  BL k

k!

Hence, Theorem 3.3 implies the following corollary.

Corollary 3.5 Let A, B be a stabilizable pair of constant matrices, with respect to a constant matrix

L satisfying the condition

p

n−1



k0

g A  BL k

k!

Then system3.32-1.2, under condition (a), is globally exponentially stabilizable by means of the

feedback law2.1.

Example 3.6 Consider the control system in R2:

x k  1  Akxk  A1kxk − 2  Bkuk, 3.35

where Ak a1k a2k



, A1k 



d1k d2k

d3k d4k



, and Bb 0

0 0

 , subject to the initial conditions

where ϕk is a given function with values in R2, a1k, a2k are positive scalar-valued

bounded sequences with the property

q ≡ sup

k≥0{|a1k  1 − a1k|  |a2k  1 − a2k|} < ∞, 3.37

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and d i k, i  1, , 4, are positive scalar-valued sequences with

p sup

k≥0

4

i1

|d i k|



In the present case, the pairAk, B is controllable Take

L k  L 



l1 l2

0 0



Then

C L k 



β k ωk



where βk  bl1 a1k and ωk  bl2 a2k > 0.

By inequality

g A ≤ √1

it follows that

v L ≤ vl1, l2 : 1  sup

k≥0

Assume that

ρ L  ρl1l2  sup

k≥0





β k2 



β2k

1/2





< 1. 3.43

Since Bk and Lk are constants, by 3.37 we have q L  q Hence, according to 3.28,

S C L , A1 ≤ Sl1, l2  q

1− ρl1, l2 2  p

1− ρl1, l2

 vl1, l2

#

2q

1− ρl1, l2 3  p

1− ρl1, l2 2

$

.

3.44

If q and p are small enough such that for some l1 and l2 we have Sl1, l2 < 1,

then by Theorem 3.3, system 3.35-3.36, under conditions 3.37 and 3.38, is globally exponentially stabilizable

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In the same way,Theorem 3.3can be extended to the discrete-time control system with multiple delays

x k  1  Akxk N

i1

x k  ϕk, k ∈ {−r N , −r N  1, , 0}, 3.46

where A i i  1, , N are variable n × n matrices, 1 ≤ r1≤ r2≤ · · · ≤ r N ; N ≥ 1.

Denote

p N

i1

sup

k≥0A i k, γ  p max

−r N ≤k≤0 ψ k ∞

k0

sup

l 0,1,

T k l 3.47

Theorem 3.7 Let Ak, Bk be stabilizable for each k ∈ Z with respect to a matrix function

L k satisfying the conditions (i), (ii), and (iii) In addition, assume that

p N

i1

sup

If

SC L ,Σ n−1

k0

v k L

k!



k  1q L

1− ρ L k2 p

1− ρ L k1



< 1, 3.49

then system3.45-3.46 is globally exponentially stabilizable by means of the feedback law 2.1.

Moreover, any solution of 3.45-3.46 satisfies the inequality

xk ≤ M0 ϕ0  γ

As an application, one consider, the stabilization of the nonlinear discrete-time control system

x k  1  Akxk  A1kxk − r  Bkuk  fk, xk, xk − r, uk, 3.51

where f : Z× C n × C n × C m → C n m ≤ n is a given nonlinear function satisfying

f

for some positive numbers a, b, and c.

...

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In the same way,Theorem 3.3can be extended to the discrete-time control system with multiple delays...

k≥0

Trang 7

where ρ Tk is the spectral radius of Tk for each k ∈ Z...

Trang 10

and d i k, i  1, , 4, are positive scalar-valued sequences with< /i>

p

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