Some properties of solutions of a functional-differential equation of second order with delay

Abstract

Existence, uniqueness, data dependence (monotony, continuity, and  differentiability with respect to parameter), and Ulam-Hyers stability results for the solutions of a system of functional-differential equations with delays are proved. The techniques used are Perov’s fixed point theorem and weakly Picard operator theory.

Authors

V.A. Ilea
(Babes Bolyai Univ)

D. Otrocol
(Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy)

Diana Otrocol


Keywords

System of functional-differential equations, delay, existence, uniqueness, data dependence, Ulam-Hyers stability, weakly Picard operator technique

Cite this paper as:

V. A. Ilea, D. Otrocol, Some properties of solutions of a functional-differential equation of second order with delay, Hindawi Publishing Corporation, Sci. World J., Vol. 2014 (2014), Article ID 878395, 8 pages, doi: 10.1155/2014/878395

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Scientific world Journal

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Hindawi Publishing Corporation, New York, USA

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1537-744X

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Some properties of solutions of a functional-differential equation of second order with delay

Veronica Ana Ilea∗ and Diana Otrocol∗∗
Abstract.

Existence, uniqueness, data dependence (monotony, continuity, differentiability with respect to parameter) and Ulam-Hyers stability results for the solutions of a system of functional-differential equations with delays are proved. The techniques used are Perov’s fixed point theorem and weakly Picard operator theory.

2010 Mathematics Subject Classification: 47H10, 34K40, 34L05, 34K20.
Key words and phrases: Perov’s fixed point theorem, weakly Picard operators, data dependence, Ulam-Hyers stability.
∗Babeş-Bolyai University, Kogălniceanu no. 1, Cluj-Napoca, Romania, e-mail: vdarzu@math.ubbcluj.ro.
∗∗“T. Popoviciu” Institute of Numerical Analysis, Romanian Academy, P.O.Box. 68-1, 400110, Cluj-Napoca, Romania, e-mail: dotrocol@ictp.acad.ro (Corresponding author).
The work of the first author was supported by a grant of the Romanian National Authority for Scientific Research, CNCS – UEFISCDI, project number PN-II-ID-PCE-2011-3-0094.

1. Introduction

Functional-differential equations with delay arise when modeling biological, physical, engineering, etc., processes whose rate of change of state at any moment of time tt is determined not only by the present state, but also by past state.

The description of certain phenomena in physics has to take into account that the rate of propagation is finite. For example, oscillation in a vacuum tube can be described by the following equation in dimensionless variables [4], [9]

x′′​(t)+2​r​x′​(t)+ω2​x​(t)+2​q​x′​(t−1)=ϵ​x′⁣3​(t−1).x^{\prime\prime}(t)+2rx^{\prime}(t)+\omega^{2}x(t)+2qx^{\prime}(t-1)=\epsilon x^{\prime 3}(t-1).

In this equation, time delay is due to the fact that the time necessary for electrons to pass from the cathode to the anode in the tube is finite. The same equation has been used in the theory of stabilization of ships [9]. The dynamics of an autogenerator with delay and second-order filter was described in [1] by the equation

x′′​(t)+2​δ​x′​(t)+x​(t)=f​(x​(t−h)).x^{\prime\prime}(t)+2\delta x^{\prime}(t)+x(t)=f(x(t-h)).

The model of ship course stabilization under conditions of uncertainty may be described by the following equation [3],

I​x′′​(t)+H​x′​(t)=−K​Ψ​(t)+b0​ξ0′​(t),x​(t0)=x0,x′​(t0)=0,Ix^{\prime\prime}(t)+Hx^{\prime}(t)=-K\Psi(t)+b_{0}\xi_{0}^{\prime}(t),\ x(t_{0})=x_{0},\ x^{\prime}(t_{0})=0,

with x​(t)x(t) being the angle of the deviation from course, Ψ​(t)\Psi(t) the turning angle of the rudder and ξ0​(t)\xi_{0}(t) the stochastic disturbance. In the process of mathematical modeling often small delays are neglected, that’s why sometimes it appears false conclusions. As an example we can give the following equation [4],

x′′​(t)+x′​(t)+x​(t)=a​[x′′​(t−h)+x′​(t−h)+x​(t−h)],x^{\prime\prime}(t)+x^{\prime}(t)+x(t)=a[x^{\prime\prime}(t-h)+x^{\prime}(t-h)+x(t-h)],

which is asymptotically stable for h=0h=0, but unstable for arbitrary h>0h>0. Here a>1a>1. If h=0h=0 the above system is asymptotically stable. The characteristic equation is Δ​(z)=(z2+z+1)​(1−a​e−h​z)=0\Delta(z)=(z^{2}+z+1)(1-ae^{-hz})=0 has the solutions with Δ\Delta the positive real part of h>0h>0. So the trivial solution is unstable for any h>0h>0.

In this paper we continue the research in this field and develop the study of the following general functional differential equation with delay

(1.1) {x′′​(t)=f​(t,x​(t),x′​(t),x​(t−h),x′​(t−h)),t∈[a,b]x​(t)=φ​(t),t∈[a−h,a].\left\{\begin{array}[c]{l}x^{\prime\prime}(t)=f(t,x(t),x^{\prime}(t),x(t-h),x^{\prime}(t-h)),\ t\in[a,b]\\ x(t)=\varphi(t),\ t\in[a-h,a].\end{array}\right.

Existence, uniqueness, data dependence (monotony, continuity, differentiability with respect to parameter) and Ulam-Hyers stability results of solution for the Cauchy problem are obtained. Our results are essentially based on Perov’s fixed point theorem and weakly Picard operator technique, which will be presented in Section 2. More results about functional and integral differential equations using these techniques can be found in [2], [5]-[7]. The problem (1.1) is equivalent to the following system

(1.2) {x′​(t)=z​(t),t∈[a,b]z′​(t)=f​(t,x​(t),z​(t),x​(t−h),z​(t−h)),t∈[a,b],\left\{\begin{array}[c]{l}x^{\prime}(t)=z(t),\ t\in[a,b]\\ z^{\prime}(t)=f(t,x(t),z(t),x(t-h),z(t-h)),\ t\in[a,b],\end{array}\right.

with the initial conditions

(1.3) {x​(t)=φ​(t),t∈[a−h,a]z​(t)=φ′​(t),t∈[a−h,a].\left\{\begin{array}[c]{c}x(t)=\varphi(t),\ t\in[a-h,a]\\ z(t)=\varphi^{\prime}(t),\ t\in[a-h,a].\end{array}\right.

By a solution of the system (1.2) we understand a function (xz)∈C​([a−h,b],ℝ2)∩C1​([a,b],ℝ2)\binom{x}{z}\in\linebreak C([a-h,b],\mathbb{R}^{2})\cap C^{1}([a,b],\mathbb{R}^{2}) that verifies the system.

We suppose that

  1. (C1)

    a<b,h>0;a<b,\ h>0;

  2. (C2)

    f∈C​([a,b]×ℝ4,ℝ),φ∈C1​([a−h,a],ℝ);f\in C([a,b]\times\mathbb{R}^{4},\mathbb{R}),\varphi\in C^{1}([a-h,a],\mathbb{R});

  3. (C3)

    there exists L1,L2>0L_{1},L_{2}>0 such that ∀t∈[a,b],ui,vi,u~i,v~i∈ℝ,i=1,2,\forall t\in[a,b],u_{i},v_{i},\widetilde{u}_{i},\widetilde{v}_{i}\in\mathbb{R},\linebreak i\mathbb{=}1,2, we have

    |f​(t,u1,v1,u2,v2)−f​(t,u~1,v~1,u~2,v~2)|≤\displaystyle\left|f(t,u_{1},v_{1},u_{2},v_{2})-f(t,\widetilde{u}_{1},\widetilde{v}_{1},\widetilde{u}_{2},\widetilde{v}_{2})\right|\leq
    ≤L1​max⁡(|u1−u~1|,|u2−u~2|)+L2​max⁡(|v1−v~1|,|v2−v~2|).\displaystyle\leq L_{1}\max\left(\left|u_{1}-\widetilde{u}_{1}\right|,\left|u_{2}-\widetilde{u}_{2}\right|\right)+L_{2}\max\left(\left|v_{1}-\widetilde{v}_{1}\right|,\left|v_{2}-\widetilde{v}_{2}\right|\right).

If (xz)∈C​([a−h,b],ℝ2)∩C1​([a,b],ℝ2)\binom{x}{z}\in C([a-h,b],\mathbb{R}^{2})\cap C^{1}([a,b],\mathbb{R}^{2}) is a solution of the problem (1.2)-(1.3) then (xz)\binom{x}{z} is a solution of the following integral system

(1.4) (xz)​(t)={(φφ′)​(t), for ​t∈[a−h,a](φ​(a)+∫atz​(s)​𝑑sφ′​(a)+∫atf​(s,x​(s),z​(s),x​(s−h),z​(s−h))​𝑑s), for ​t∈[a,b].\binom{x}{z}(t)=\left\{\begin{array}[c]{l}\binom{\varphi}{\varphi^{\prime}}(t),\text{ for }t\in[a-h,a]\\ \binom{\varphi(a)+\int_{a}^{t}z(s)ds}{\varphi^{\prime}(a)+\int_{a}^{t}f(s,x(s),z(s),x(s-h),z(s-h))ds},\text{ for }t\in[a,b].\end{array}\right.

If (xz)∈C​([a−h,b],ℝ2)\binom{x}{z}\in C([a-h,b],\mathbb{R}^{2}) is a solution of (1.4) then (xz)∈C​([a−h,b],ℝ2)∩C1​([a,b],ℝ2)\binom{x}{z}\in C([a-h,b],\linebreak\mathbb{R}^{2})\cap C^{1}([a,b],\mathbb{R}^{2}) and (xz)\binom{x}{z}\ is a solution of (1.2)-(1.3).

Moreover, the system (1.2) is equivalent to the functional integral system

(1.5) (xz)​(t)={(xz)​(t), for ​t∈[a−h,a](x​(a)+∫atz​(s)​𝑑sz​(a)+∫atf​(s,x​(s),z​(s),x​(s−h),z​(s−h))​𝑑s), for ​t∈[a,b].\binom{x}{z}(t)=\left\{\begin{array}[c]{l}\binom{x}{z}(t),\text{ for }t\in[a-h,a]\\ \binom{x(a)+\int_{a}^{t}z(s)ds}{z(a)+\int_{a}^{t}f(s,x(s),z(s),x(s-h),z(s-h))ds},\text{ for }t\in[a,b].\end{array}\right.

We consider the operators B,E:C​([a−h,b],ℝ2)→C​([a−h,b],ℝ2),B=(B1​(xz)B2​(xz)),E=(E1​(xz)E2​(xz))B,E:C([a-h,b],\mathbb{R}^{2})\rightarrow C([a-h,b],\mathbb{R}^{2}),\ B=\binom{B_{1}\binom{x}{z}}{B_{2}\binom{x}{z}},\ E=\binom{E_{1}\binom{x}{z}}{E_{2}\binom{x}{z}} defined by B​(xz)​(t):=B\binom{x}{z}(t):=the right hand side of (1.4), for t∈[a−h,b]t\in[a-h,b] and E​(xz)​(t):=E\binom{x}{z}(t):=the right hand side of (1.5), for t∈[a−h,b].t\in[a-h,b].

2. Preliminaries

In this section, we introduce notations, definitions, and preliminary results which are used throughout this paper, see [10]–[18]. Let (X,d)(X,d) be a metric space and A:X→XA:X\rightarrow X an operator. We shall use the following notations:

FA:={x∈X∣A​(x)=x}F_{A}:=\{x\in X\mid A(x)=x\} - the fixed points set of AA;

I​(A):={Y⊂X∣A​(Y)⊂Y,Y≠∅}I(A):=\{Y\subset X\mid A(Y)\subset Y,Y\neq\emptyset\} - the family of the nonempty invariant subset of AA;

An+1:=A∘An,A0=1X,A1=A,n∈ℕA^{n+1}:=A\circ A^{n},\;A^{0}=1_{X},\;A^{1}=A,\;n\in\mathbb{N}.

Definition 2.1.

Let (X,d)(X,d) be a metric space. An operator A:X→XA:X\rightarrow X is a Picard operator (PO) if there exists x∗∈Xx^{\ast}\in X such that:

  • (i)

    FA={x∗};F_{A}=\{x^{\ast}\};

  • (ii)

    the sequence (An​(x0))n∈ℕ(A^{n}(x_{0}))_{n\in\mathbb{N}} converges to x∗x^{\ast} for all x0∈Xx_{0}\in X.

Definition 2.2.

Let (X,d)(X,d) be a metric space. An operator A:X→XA:X\rightarrow X is a weakly Picard operator (WPO) if the sequence (An​(x))n∈ℕ(A^{n}(x))_{n\in\mathbb{N}} converges for all x∈Xx\in X, and its limit (which may depend on xx) is a fixed point of AA.

Definition 2.3.

If AA is weakly Picard operator then we consider the operator A∞A^{\infty} defined by

A∞:X→X,A∞​(x):=limn→∞​An​(x).A^{\infty}:X\rightarrow X,\ A^{\infty}(x):=\underset{n\rightarrow\infty}{\lim}A^{n}(x).
Remark 2.4.

It is clear that A∞​(X)=FA.A^{\infty}(X)=F_{A}.

Definition 2.5.

Let AA be a weakly Picard operator and c>0.c>0. The operator AA\ is cc-weakly Picard operator if

d​(x,A∞​(x))≤c​d​(x,A​(x)),∀x∈X.d(x,A^{\infty}(x))\leq cd(x,A(x)),\ \forall x\in X.

The following concept is important for our further considerations.

Definition 2.6.

Let (X,d)(X,d) be a metric space and f:X→Xf:X\rightarrow X be an operator. The fixed point equation

(2.1) x=f​(x)x=f(x)

is Ulam-Hyers stable if there exists a real number cf>0c_{f}>0 such that: for each ε>0\varepsilon>0 and each solution y∗y^{\ast} of the inequation

d​(y,f​(y))≤εd(y,f(y))\leq\varepsilon

there exists a solution x∗x^{\ast} of the equation (2.1) such that

d​(y∗,x∗)≤cf​ε.d(y^{\ast},x^{\ast})\leq c_{f}\varepsilon.

Now we have

Theorem 2.7.

[18] If f:X→Xf:X\rightarrow X is cc-WPO, then the equation

x=f​(x)x=f(x)

is Ulam-Hyers stable.

Another result from the WPO theory is the following (see, e.g., [12]).

Theorem 2.8.

(Fibre contraction principle). Let (X,d)(X,d) and (Y,ρ)(Y,\rho) be two metric spaces and A:X×Y→X×Y,A=(B,C),(B:X→X,C:X×Y→Y)A:X\times Y\rightarrow X\times Y,\ A=(B,C),\ (\ B:X\rightarrow X,\ C:X\times Y\rightarrow Y\ ) a triangular operator. We suppose that

  1. (i)

    (Y,ρ)(Y,\rho) is a complete metric space;

  2. (ii)

    the operator BB is Picard operator;

  3. (iii)

    there exists l∈[0,1)l\in[0,1) such that C​(x,⋅):Y→YC(x,\cdot):Y\rightarrow Y is a ll-contraction, for all x∈Xx\in X;

  4. (iv)

    if (x∗,y∗)∈FA(x^{\ast},y^{\ast})\in F_{A}, then C​(⋅,y∗)C(\cdot,y^{\ast}) is continuous in x∗x^{\ast}.

Then the operator AA is Picard operator.

Throughout this paper we denote by Mm​m​(ℝ+)M_{mm}(\mathbb{R}_{+}) the set of all m×mm\times m matrices with positive elements and by II the identity m×mm\times m matrix. A square matrix QQ with nonnegative elements is said to be convergent to zero if Qk→0Q^{k}\rightarrow 0 as k→∞k\rightarrow\infty. It is known that the property of being convergent to zero is equivalent to each of the following three conditions (see [10], [11]):

  • (a)

    I−QI-Q is nonsingular and (I−Q)−1=I+Q+Q2+⋯(I-Q)^{-1}=I+Q+Q^{2}+\cdots (where II stands for the unit matrix of the same order as QQ);

  • (b)

    the eigenvalues of QQ are located inside the open unit disc of the complex plane;

  • (c)

    I−QI-Q is nonsingular and (I−Q)−1(I-Q)^{-1} has nonnegative elements.

We finish this section by recalling the following fundamental result (see [8], [10]).

Theorem 2.9.

(Perov’s fixed point theorem). Let (X,d)(X,d) with d​(x,y)∈ℝmd(x,y)\in\mathbb{R}^{m}, be a complete generalized metric space and A:X→XA:X\rightarrow X an operator. We suppose that there exists a matrix Q∈Mm​m​(ℝ+)Q\in M_{mm}(\mathbb{R}_{+}), such that

  • (i)

    d​(A​(x),A​(y))≤Q​d​(x,y)d(A(x),A(y))\leq Qd(x,y), for all x,y∈X;x,y\in X;

  • (ii)

    Qn→0Q^{n}\rightarrow 0 as n→∞n\rightarrow\infty.

Then

  • (a)

    FA={x∗};F_{A}=\{x^{\ast}\};

  • (b)

    An​(x)=x∗A^{n}(x)=x^{\ast} as n→∞n\rightarrow\infty, ∀x∈X;\forall x\in X;

  • (c)

    d​(An​(x),x∗)≤(I−Q)−1​Qn​d​(x0,A​(x0))d(A^{n}(x),x^{\ast})\leq(I-Q)^{-1}Q^{n}d(x_{0},A(x_{0})).

3. Main results

In this section we present existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results of solution for the Cauchy problem (1.2)-(1.3).

3.1. Existence and uniqueness

Using Perov’s fixed point theorem we obtain existence and uniqueness theorem for the solution of the problem (1.2)-(1.3).

Theorem 3.1.

We suppose that:

  • (i)

    the conditions (C1)-(C3) are satisfied;

  • (ii)

    Qn→0Q^{n}\rightarrow 0 as n→∞,n\rightarrow\infty, where Q=(b−a)​(01L1L2)Q=(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right).

Then:

  • (a)

    the problem (1.2)-(1.3) has a unique solution (x∗z∗)∈C1​([a,b],ℝ2);\binom{x^{\ast}}{z^{\ast}}\in C^{1}([a,b],\mathbb{R}^{2});

  • (b)

    for all (x0z0)∈C1​([a,b],ℝ2)\binom{x^{0}}{z^{0}}\in C^{1}([a,b],\mathbb{R}^{2}), the sequence (xnzn)n∈ℕ\binom{x^{n}}{z^{n}}_{n\in\mathbb{N}} defined by(xn+1zn+1)=B​(xnzn)\ \binom{x^{n+1}}{z^{n+1}}=B\binom{x^{n}}{z^{n}}, converges uniformly to (x∗z∗)\binom{x^{\ast}}{z^{\ast}}, for all t∈[a,b],t\in[a,b], and

    ‖(xnzn)−(x∗z∗)‖≤(I−Q)−1​Qn​‖(x0z0)−(x1z1)‖;\left\|\binom{x^{n}}{z^{n}}-\binom{x^{\ast}}{z^{\ast}}\right\|\leq(I-Q)^{-1}Q^{n}\left\|\binom{x^{0}}{z^{0}}-\binom{x^{1}}{z^{1}}\right\|;
  • (c)

    the operator BB is Picard operator in (C​([a−h,b],ℝ2),⟶u​n​i​f)(C([a-h,b],\mathbb{R}^{2}),\overset{unif}{\longrightarrow});

  • (d)

    the operator EE is weakly Picard operator in (C​([a−h,b],ℝ2),⟶u​n​i​f)(\!C([a\!-\!h,b],\mathbb{R}^{2}),\!\!\overset{unif}{\longrightarrow}\!).

Proof.

Consider on the space X:=C​([a−h,b],ℝ2)X:=C([a-h,b],\mathbb{R}^{2}) the norm

‖(u1v1)−(u2v2)‖:=max⁡(|u1−u2||v1−v2|),\left\|\binom{u_{1}}{v_{1}}-\binom{u_{2}}{v_{2}}\right\|:=\max\binom{\left|u_{1}-u_{2}\right|}{\left|v_{1}-v_{2}\right|},

which endows XX with the uniform convergence.

Let X(χχ′)={(xz)∈X|(xz)|[a−h,a]=(χχ′)​, for ​(χχ′)∈C​([a−h,a],ℝ2)}.X_{\binom{\chi}{\chi^{\prime}}}=\left\{\binom{x}{z}\in X|\left.\binom{x}{z}\right|_{[a-h,a]}=\binom{\chi}{\chi^{\prime}}\text{, for }\binom{\chi}{\chi^{\prime}}\in C([a-h,a],\mathbb{R}^{2})\right\}. Then X=∪(χχ′)∈C​([a−h,a],ℝ2)​X(χχ′)X=\underset{\binom{\chi}{\chi^{\prime}}\in C([a-h,a],\mathbb{R}^{2})}{\cup}X_{\binom{\chi}{\chi^{\prime}}} is a partition of XX and from [13] we have

  • (1)

    B​(X)⊂X(χχ′),B​(X(χχ′))⊂X(χχ′);B(X)\subset X_{\binom{\chi}{\chi^{\prime}}},B(X_{\binom{\chi}{\chi^{\prime}}})\subset X_{\binom{\chi}{\chi^{\prime}}};

  • (2)

    B|X(χχ′)=E|X(χχ′).B|_{X_{\binom{\chi}{\chi^{\prime}}}}=E|_{X_{\binom{\chi}{\chi^{\prime}}}}.

On the other hand, for t∈[a−h,a]∪[a,b]t\in[a-h,a]\cup[a,b]

‖(B1​(x1z1)B2​(x1z1))−(B1​(x2z2)B2​(x2z2))‖≤(b−a)​(01L1L2)​‖(x1z1)−(x2z2)‖,\left\|\binom{B_{1}\binom{x_{1}}{z_{1}}}{B_{2}\binom{x_{1}}{z_{1}}}-\binom{B_{1}\binom{x_{2}}{z_{2}}}{B_{2}\binom{x_{2}}{z_{2}}}\right\|\leq(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right)\left\|\binom{x_{1}}{z_{1}}-\binom{x_{2}}{z_{2}}\right\|,

whence BB is a contraction in (X,∥⋅∥)(X,\left\|\cdot\right\|) with Q=(b−a)​(01L1L2)Q=(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right). Applying Perov’s theorem we obtain (a), (b) and (c). Moreover the operator BB is cc-PO and EE is cc-WPO with c=[1−(b−a)​(01L1L2)]−1.c=\left[1-(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right)\right]^{-1}. ∎

3.2. Inequalities of Čaplygin type

Now we establish the Čaplygin type inequalities.

Theorem 3.2.

We suppose that

  • (i)

    the conditions (a), (b) and (c) in Theorem 3.1 are satisfied;

  • (ii)

    ui,vi,u~i,v~i∈ℝ,u_{i},v_{i},\widetilde{u}_{i},\widetilde{v}_{i}\in\mathbb{R}, (uivi)≤(u~iv~i),i=1,2\binom{u_{i}}{v_{i}}\leq\binom{\widetilde{u}_{i}}{\widetilde{v}_{i}},i=1,2 imply that

    f​(t,u1,v1,u2,v2)≤f​(t,u~1,v~1,u~2,v~2),∀t∈[a,b].f(t,u_{1},v_{1},u_{2},v_{2})\leq f(t,\widetilde{u}_{1},\widetilde{v}_{1},\widetilde{u}_{2},\widetilde{v}_{2}),\ \forall t\in[a,b].

Let (x∗z∗)\binom{x^{\ast}}{z^{\ast}} be a solution of (1.2) and (y∗w∗)\binom{y^{\ast}}{w^{\ast}} be a solution of the system

{y′​(t)≤w​(t),t∈[a,b]w′​(t)≤f​(t,y​(t),w​(t),y​(t−h),w​(t−h)),t∈[a,b].\left\{\begin{array}[c]{l}y^{\prime}(t)\leq w(t),\ t\in[a,b]\\ w^{\prime}(t)\leq f(t,y(t),w(t),y(t-h),w(t-h)),\ t\in[a,b].\end{array}\right.

Then

(y∗w∗)|[a−h,a]≤(x∗z∗)|[a−h,a]​ implies that ​(y∗w∗)≤(x∗z∗).\left.\binom{y^{\ast}}{w^{\ast}}\right|_{[a-h,a]}\leq\left.\binom{x^{\ast}}{z^{\ast}}\right|_{[a-h,a]}\text{ implies that }\binom{y^{\ast}}{w^{\ast}}\leq\binom{x^{\ast}}{z^{\ast}}.
Proof.

We have that

(x∗z∗)=E​(x∗z∗)​, ​(y∗w∗)≤E​(y∗w∗).\binom{x^{\ast}}{z^{\ast}}=E\binom{x^{\ast}}{z^{\ast}}\text{, }\binom{y^{\ast}}{w^{\ast}}\leq E\binom{y^{\ast}}{w^{\ast}}.

From Theorem 3.1, (c), EE is weakly Picard operator. From condition (ii), we obtain that E∞E^{\infty} is increasing ([12]). So

(y∗w∗)≤E∞​(y∗w∗)=E∞​(y~∗w~∗)≤E∞​(x~∗z~∗)=(x∗z∗)\binom{y^{\ast}}{w^{\ast}}\leq E^{\infty}\binom{y^{\ast}}{w^{\ast}}=E^{\infty}\binom{\widetilde{y}^{\ast}}{\widetilde{w}^{\ast}}\leq E^{\infty}\binom{\widetilde{x}^{\ast}}{\widetilde{z}^{\ast}}=\binom{x^{\ast}}{z^{\ast}}

where (x~∗z~∗)∈X(xz)|[a−h,a].\binom{\widetilde{x}^{\ast}}{\widetilde{z}^{\ast}}\in X_{\binom{x}{z}|_{[a-h,a]}}. ∎

3.3. Data dependence: monotony

In this subsection we study the monotony of the solution of the problem (1.2)-(1.3) with respect to φ\varphi and ff.

Theorem 3.3.

(Comparison theorem) Let fi∈C​([a,b]×ℝ4,ℝ),f_{i}\in C([a,b]\times\mathbb{R}^{4},\mathbb{R}), i=1,2,3,i=1,2,3, be as in Theorem 3.1. We suppose that

  • (i)

    f1≤f2≤f3;f_{1}\leq f_{2}\leq f_{3};

  • (ii)

    f2​(t,⋅,⋅,⋅,⋅):ℝ4→ℝf_{2}(t,\cdot,\cdot,\cdot,\cdot):\mathbb{R}^{4}\rightarrow\mathbb{R} is increasing, ∀t∈[a,b].\forall t\in[a,b].

Let (xi∗zi∗)\binom{x_{i}^{\ast}}{z_{i}^{\ast}} be a solution of the system

(3.1) {x′​(t)=z​(t),t∈[a,b]z′​(t)=fi​(t,x​(t),z​(t),x​(t−h),z​(t−h)),t∈[a,b].\left\{\begin{array}[c]{l}x^{\prime}(t)=z(t),\ t\in[a,b]\\ z^{\prime}(t)=f_{i}(t,x(t),z(t),x(t-h),z(t-h)),\ t\in[a,b].\end{array}\right.

Then

(x1∗z1∗)|[a−h,a]≤(x2∗z2∗)|[a−h,a]≤(x3∗z3∗)|[a−h,a]\left.\binom{x_{1}^{\ast}}{z_{1}^{\ast}}\right|_{[a-h,a]}\leq\left.\binom{x_{2}^{\ast}}{z_{2}^{\ast}}\right|_{[a-h,a]}\leq\left.\binom{x_{3}^{\ast}}{z_{3}^{\ast}}\right|_{[a-h,a]}

imply that (x1∗z1∗)|[a−h,b]≤(x2∗z2∗)|[a−h,b]≤(x3∗z3∗)|[a−h,b]\left.\binom{x_{1}^{\ast}}{z_{1}^{\ast}}\right|_{[a-h,b]}\leq\left.\binom{x_{2}^{\ast}}{z_{2}^{\ast}}\right|_{[a-h,b]}\leq\left.\binom{x_{3}^{\ast}}{z_{3}^{\ast}}\right|_{[a-h,b]}.

Proof.

We consider the operators EiE_{i} corresponding to each system (3.1). The operators Ei,i=1,2,3E_{i},i=1,2,3 are weakly Picard operators. Taking into consideration the condition (ii), E2E_{2} is increasing. From (i) we have E1≤E2≤E3.E_{1}\leq E_{2}\leq E_{3}. On the other hand we have that

(xi∗zi∗)=Ei∞​(x~i∗z~i∗),i=1,2,3.\binom{x_{i}^{\ast}}{z_{i}^{\ast}}=E_{i}^{\infty}\binom{\widetilde{x}_{i}^{\ast}}{\widetilde{z}_{i}^{\ast}},i=1,2,3.

where (x~∗z~∗)∈X(xz)|[a−h,a]\binom{\widetilde{x}^{\ast}}{\widetilde{z}^{\ast}}\in X_{\binom{x}{z}|_{[a-h,a]}}. The proof follows from the abstract comparison Lemma (see [12]). ∎

3.4. Data dependence: continuity

Consider the problem (1.2)-(1.3) with the dates fif_{i} ∈C​([a,b]×ℝ4,ℝ),i=1,2\in C([a,b]\times\mathbb{R}^{4},\mathbb{R}),i=1,2\ and suppose that fif_{i} satisfy the conditions from Theorem 3.1 with the same Lipshitz constants. We obtain the data dependence result.

Theorem 3.4.

Let fi∈C​([a,b]×ℝ4,ℝ),φi∈C​([a−h,a],ℝ),f_{i}\in C([a,b]\times\mathbb{R}^{4},\mathbb{R}),\varphi_{i}\in C([a-h,a],\mathbb{R}), i=1,2,i=1,2, be as in Theorem 3.1. We suppose that

  • (i)

    there exists η1,η2>0\eta_{1},\eta_{2}>0 such that

    |(φ1φ1′)​(t)−(φ2φ2′)​(t)|≤(η1η2),∀t∈[a−h,a];\left|\binom{\varphi_{1}}{\varphi_{1}^{\prime}}(t)-\binom{\varphi_{2}}{\varphi_{2}^{\prime}}(t)\right|\leq\binom{\eta_{1}}{\eta_{2}},\ \forall t\in[a-h,a];
  • (ii)

    there exists η3>0\eta_{3}>0 such that

    |f1​(t,u1,u2,u3,u4)−f2​(t,u1,u2,u3,u4)|≤η3,∀t∈[a,b],ui∈ℝ,i=1,4¯.\left|f_{1}(t,u_{1},u_{2},u_{3},u_{4})-f_{2}(t,u_{1},u_{2},u_{3},u_{4})\right|\leq\eta_{3},\forall t\in[a,b],u_{i}\in\mathbb{R},i\mathbb{=}\overline{1,4}.

Then

‖(x∗z∗)​(⋅,φ1,φ1′,f1)−(x∗z∗)​(⋅,φ2,φ2′,f2)‖≤(I−Q)−1​(η1η2+(b−a)​η3),\left\|\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})-\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right\|\leq(I-Q)^{-1}\binom{\eta_{1}}{\eta_{2}+(b-a)\eta_{3}},

where (x∗z∗)​(⋅,φ,φ′,f)\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi,\varphi^{\prime},f) denote the unique solution of (1.2)-(1.3).

Proof.

Consider the operators Bφi,fi,i=1,2.B_{\varphi_{i},f_{i}},i=1,2. From Theorem 3.1 it follows

‖Bφ1,f1​(x1z1)−Bφ1,f1​(x2z2)‖≤Q​‖(x1z1)−(x2z2)‖,∀(xizi)∈X.\left\|B_{\varphi_{1},f_{1}}\binom{x_{1}}{z_{1}}-B_{\varphi_{1},f_{1}}\binom{x_{2}}{z_{2}}\right\|\leq Q\left\|\binom{x_{1}}{z_{1}}-\binom{x_{2}}{z_{2}}\right\|,\forall\binom{x_{i}}{z_{i}}\in X.

Additionally,

‖Bφ1,f1​(xz)−Bφ2,f2​(xz)‖≤(η1η2+(b−a)​η3).\left\|B_{\varphi_{1},f_{1}}\binom{x}{z}-B_{\varphi_{2},f_{2}}\binom{x}{z}\right\|\leq\binom{\eta_{1}}{\eta_{2}+(b-a)\eta_{3}}.

Thus

‖(x∗z∗)​(⋅,φ1,φ1′,f1)−(x∗z∗)​(⋅,φ2,φ2′,f2)‖\displaystyle\left\|\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})-\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right\|
=‖Bφ1,f1​((x∗z∗)​(⋅,φ1,φ1′,f1))−Bφ2,f2​((x∗z∗)​(⋅,φ2,φ2′,f2))‖\displaystyle=\left\|B_{\varphi_{1},f_{1}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})\right)-B_{\varphi_{2},f_{2}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right)\right\|
≤‖Bφ1,f1​((x∗z∗)​(⋅,φ1,φ1′,f1))−Bφ1,f1​((x∗z∗)​(⋅,φ2,φ2′,f2))‖\displaystyle\leq\left\|B_{\varphi_{1},f_{1}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})\right)-B_{\varphi_{1},f_{1}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right)\right\|
+‖Bφ1,f1​((x∗z∗)​(⋅,φ2,φ2′,f2))−Bφ2,f2​((x∗z∗)​(⋅,φ2,φ2′,f2))‖\displaystyle\quad+\left\|B_{\varphi_{1},f_{1}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right)-B_{\varphi_{2},f_{2}}\left(\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right)\right\|
≤Q​‖(x∗z∗)​(⋅,φ1,φ1′,f1)−(x∗z∗)​(⋅,φ2,φ2′,f2)‖+(η1η2+(b−a)​η3),\displaystyle\leq Q\left\|\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})-\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right\|+\binom{\eta_{1}}{\eta_{2}+(b-a)\eta_{3}},

and since Qn→∞Q^{n}\rightarrow\infty, as n→∞n\rightarrow\infty implies that (I−Q)−1∈M22​(ℝ+)(I-Q)^{-1}\in M_{22}(\mathbb{R}_{+}), we finally obtain

‖(x∗z∗)​(⋅,φ1,φ1′,f1)−(x∗z∗)​(⋅,φ2,φ2′,f2)‖≤(I−Q)−1​(η1η2+(b−a)​η3)​.\left\|\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{1},\varphi_{1}^{\prime},f_{1})-\binom{x^{\ast}}{z^{\ast}}(\cdot,\varphi_{2},\varphi_{2}^{\prime},f_{2})\right\|\leq(I-Q)^{-1}\binom{\eta_{1}}{\eta_{2}+(b-a)\eta_{3}}\text{.}

∎

3.5. Data dependence: differentiability

Consider the following differential system with parameter

(3.2) {x′​(t)=z​(t),t∈[a,b]z′​(t)=f​(t,x​(t),z​(t),x​(t−h),z​(t−h);λ),t∈[a,b],λ∈J,\left\{\begin{array}[c]{l}x^{\prime}(t)=z(t),\ t\in[a,b]\\ z^{\prime}(t)=f(t,x(t),z(t),x(t-h),z(t-h);\lambda),\ t\in[a,b],\lambda\in J,\end{array}\right.

with the initial conditions

(3.3) {x​(t)=φ​(t),t∈[a−h,a]z​(t)=φ′​(t),t∈[a−h,a],\left\{\begin{array}[c]{c}x(t)=\varphi(t),\ t\in[a-h,a]\\ z(t)=\varphi^{\prime}(t),\ t\in[a-h,a],\end{array}\right.

where J⊂ℝJ\subset\mathbb{R} is a compact interval.

Suppose that the following conditions are satisfied:

  1. (C1)

    a<b,h>0,J⊂ℝa<b,h>0,\ J\subset\mathbb{R} a compact interval;

  2. (C2)

    f∈C​([a,b]×ℝ4×J,ℝ);f\in C([a,b]\times\mathbb{R}^{4}\times J,\mathbb{R});

  3. (C3)

    φ∈C1​([a−h,a],ℝ);\varphi\in C^{1}([a-h,a],\mathbb{R});

  4. (C4)

    there exists Lf>0L_{f}>0, such that

    |∂f​(t,u1,u2,u3,u4;λ)∂ui|\displaystyle\left|\frac{\partial f(t,u_{1},u_{2},u_{3},u_{4};\lambda)}{\partial u_{i}}\right| ≤L1,u1,u3∈ℝ,i=1,3,λ∈J;\displaystyle\leq L_{1},u_{1},u_{3}\in\mathbb{R},\ i=1,3,\lambda\in J;
    |∂f​(t,u1,u2,u3,u4;λ)∂ui|\displaystyle\left|\frac{\partial f(t,u_{1},u_{2},u_{3},u_{4};\lambda)}{\partial u_{i}}\right| ≤L2,u2,u4∈ℝ,i=2,4,λ∈J;\displaystyle\leq L_{2},u_{2},u_{4}\in\mathbb{R},\ i=2,4,\lambda\in J;
  5. (C5)

    for Q=(b−a)​(01L1L2)Q=(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right) we have Qn→0Q^{n}\rightarrow 0 asn→∞.\ n\rightarrow\infty.

Then, from Theorem 3.1, we have that the problem (1.2)-(1.3) has a unique solution, (x∗z∗)∈C1​([a,b],ℝ2).\binom{x^{\ast}}{z^{\ast}}\in C^{1}([a,b],\mathbb{R}^{2}). We prove that (x∗z∗)∈C1​(J,ℝ2), ​∀ ​t∈[a−h,b].\binom{x^{\ast}}{z^{\ast}}\in C^{1}(J,\mathbb{R}^{2}),\text{ }\forall\text{ }t\in[a-\!h,b].

For this we consider the system

(3.4) {x′​(t;λ)=z​(t;λ),t∈[a,b],λ∈Jz′​(t;λ)=f​(t,x​(t;λ),z​(t;λ),x​(t−h;λ),z​(t−h;λ);λ),t∈[a,b],λ∈J\left\{\begin{array}[c]{l}x^{\prime}(t;\lambda)=z(t;\lambda),\ t\in[a,b],\lambda\in J\\ z^{\prime}(t;\lambda)=f(t,x(t;\lambda),z(t;\lambda),x(t-h;\lambda),z(t-h;\lambda);\lambda),\ t\in[a,b],\lambda\in J\end{array}\right.

with (x∗z∗)∈C​([a−h,b]×J,ℝ2)∩C1​([a,b]×J,ℝ2).\binom{x^{\ast}}{z^{\ast}}\in C([a-h,b]\times J,\mathbb{R}^{2})\cap C^{1}([a,b]\times J,\mathbb{R}^{2}).

Theorem 3.5.

Consider the problem (3.4)-(3.3) and suppose the conditions (C1{}_{\text{1}})–(C5{}_{\text{5}}) hold. Then,

  1. (i)

    (3.4)-(3.3) has a unique solution (x∗z∗)​(⋅,λ)\binom{x^{\ast}}{z^{\ast}}(\!\cdot,\lambda\!), in C​([a−h,b]×J,ℝ2);C([a-h,b]\times J,\mathbb{R}^{2});

  2. (ii)

    (x∗z∗)​(⋅,λ)∈C1​(J,ℝ2),\binom{x^{\ast}}{z^{\ast}}(\!\cdot,\lambda\!)\in C^{1}(J,\mathbb{R}^{2}), ∀t∈[a−h,b].\forall t\in[a-\!h,b].

Proof.

The problem (3.4)-(3.3) is equivalent with the following functional-integral system

(3.5) (xz)​(t;λ)=(φ​(a)+∫atz​(s;λ)​𝑑sφ′​(a)+∫atf​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)​𝑑s),\binom{x}{z}(t;\lambda)=\binom{\varphi(a)+\int_{a}^{t}z(s;\lambda)ds}{\varphi^{\prime}(a)+\int_{a}^{t}f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)ds},

for t∈[a,b]t\in[a,b] and

(3.6) (xz)​(t;λ)=(φφ′)​(t), for ​t∈[a−h,a]​.\binom{x}{z}(t;\lambda)=\binom{\varphi}{\varphi^{\prime}}(t),\text{ for }t\in[a-h,a]\text{.}

Now let take the operator A:C​([a−h,b]×J,ℝ2)→C​([a−h,b]×J,ℝ2)A:C([a-h,b]\times J,\mathbb{R}^{2})\rightarrow C([a-h,b]\times J,\mathbb{R}^{2}), defined by

A​(xz)​(t;λ):=(A1​(xz)A2​(xz)):=the right hand side of (3.5), for ​t∈[a,b]​ andA\binom{x}{z}(t;\lambda):=\binom{A_{1}\binom{x}{z}}{A_{2}\binom{x}{z}}:=\text{the right hand side of (\ref{diff3}), for }t\in[a,b]\text{ and}
A​(xz)​(t;λ):=(A1​(xz)A2​(xz)):=the right hand side of (3.6), for ​t∈[a−h,a].A\binom{x}{z}(t;\lambda):=\binom{A_{1}\binom{x}{z}}{A_{2}\binom{x}{z}}:=\text{the right hand side of (\ref{diff4}), for }t\in[a-h,a].

Let X=C​([a−h,b]×J,ℝ2).X=C([a-h,b]\times J,\mathbb{R}^{2}).

It is clear, from the proof of the Theorem 3.1, that in the condition (C1{}_{\text{1}})–(C5{}_{\text{5}}), the operatorA:(X,∥⋅∥)→(X,∥⋅∥)A:(X,\left\|\cdot\right\|)\rightarrow(X,\left\|\cdot\right\|) is Picard operator.

Let (x∗z∗)\binom{x^{\ast}}{z^{\ast}} be the unique fixed point of A.A.

Supposing that there exists (∂x∗∂λ∂z∗∂λ)\dbinom{\tfrac{\partial x^{\ast}}{\partial\lambda}}{\tfrac{\partial z^{\ast}}{\partial\lambda}}, from (3.5)-(3.6), we obtain that

∂x∗∂λ=∫at∂z​(s;λ)∂λ​𝑑s\tfrac{\partial x^{\ast}}{\partial\lambda}=\int_{a}^{t}\frac{\partial z(s;\lambda)}{\partial\lambda}ds

and

∂z∗∂λ\displaystyle\tfrac{\partial z^{\ast}}{\partial\lambda} =∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u1​∂x​(s;λ)∂λ​𝑑s\displaystyle=\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{1}}\frac{\partial x(s;\lambda)}{\partial\lambda}ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u2​∂z​(s;λ)∂λ​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{2}}\frac{\partial z(s;\lambda)}{\partial\lambda}ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u3​∂x​(s−h;λ)∂λ​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{3}}\frac{\partial x(s-h;\lambda)}{\partial\lambda}ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u4​∂z​(s−h;λ)∂λ​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{4}}\frac{\partial z(s-h;\lambda)}{\partial\lambda}ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂λ​𝑑s,\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial\lambda}ds,

for all t∈[a,b],λ∈J.t\in[a,b],\lambda\in J.

This relation suggest us to consider the following operator

C\displaystyle C :X×X→X,\displaystyle:X\times X\rightarrow X,
((x12z12),(u13u24))\displaystyle\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right) →C​((x12z12),(u13u24)),\displaystyle\rightarrow C\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right),

where C​((x12z12),(u13u24))​(t;λ)=0C\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)(t;\lambda)\!=0 for t∈[a−h,a],λ∈Jt\in[a-h,a],\lambda\in J and

C​((x12z12),(u13u24))​(t;λ):=(C1​((x12z12),(u13u24))C2​((x12z12),(u13u24)))C\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)(t;\lambda)\!:=\binom{C_{1}\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)}{C_{2}\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)}

where

C1​((x12z12),(u13u24))​(t;λ):=∫at∂z​(s;λ)∂λ​𝑑sC_{1}\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)(t;\lambda):=\int_{a}^{t}\frac{\partial z(s;\lambda)}{\partial\lambda}ds

and

C2​((x12z12),(u13u24))​(t;λ)\displaystyle C_{2}\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)(t;\lambda)
:=∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u1​u1​(s;λ)​𝑑s\displaystyle:=\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{1}}u_{1}(s;\lambda)ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u2​u2​(s;λ)​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{2}}u_{2}(s;\lambda)ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u3​u3​(s−h;λ)​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{3}}u_{3}(s-h;\lambda)ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂u4​u4​(s−h;λ)​𝑑s\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial u_{4}}u_{4}(s-h;\lambda)ds
+∫at∂f​(s,x​(s;λ),z​(s;λ),x​(s−h;λ),z​(s−h;λ);λ)∂λ​𝑑s,\displaystyle\quad+\int_{a}^{t}\frac{\partial f(s,x(s;\lambda),z(s;\lambda),x(s-h;\lambda),z(s-h;\lambda);\lambda)}{\partial\lambda}ds,

for t∈[a,b],λ∈J.t\in[a,b],\lambda\in J. Here we use the notations u1​(s;λ):=∂x​(s;λ)∂λ,u2​(s;λ):=∂z​(s;λ)∂λ,u3​(s−h;λ):=∂x​(s−h;λ)∂λu_{1}(s;\lambda):=\frac{\partial x(s;\lambda)}{\partial\lambda},\ u_{2}(s;\lambda):=\frac{\partial z(s;\lambda)}{\partial\lambda},\ u_{3}(s-h;\lambda):=\frac{\partial x(s-h;\lambda)}{\partial\lambda} and u4​(s−h;λ):=∂z​(s−h;λ)∂λ.u_{4}(s-h;\lambda):=\frac{\partial z(s-h;\lambda)}{\partial\lambda}.

In this way we have the triangular operator D:X×X→X×X,((x12z12),(u13u24))→(A​(x12z12),C​((x12z12),(u13u24)))D:X\times X\rightarrow X\times X,\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)\!\rightarrow\left(A\binom{x_{12}}{z_{12}},C\left(\binom{x_{12}}{z_{12}},\binom{u_{13}}{u_{24}}\right)\right), where AA is Picard operator and C​((x12z12),(⋅⋅)):X→XC(\binom{x_{12}}{z_{12}},\binom{\cdot}{\cdot}):X\rightarrow X is QCQ_{C} -contraction with QC=(b−a)​(01L1L2)Q_{C}=(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right).

From Theorem 2.8 the operator DD is Picard operator, i.e. the sequences

(x12n+1z12n+1)\displaystyle\binom{x_{12}^{n+1}}{z_{12}^{n+1}}\! :=A​(x12nz12n),\displaystyle:=\!A\binom{x_{12}^{n}}{z_{12}^{n}},
(u13n+1u24n+1)\displaystyle\binom{u_{13}^{n+1}}{u_{24}^{n+1}} :=C​((x12nz12n),(u13nu24n)),\displaystyle:=\!C\left(\binom{x_{12}^{n}}{z_{12}^{n}},\binom{u_{13}^{n}}{u_{24}^{n}}\right),

n∈ℕn\in\mathbb{N}, converges uniformly, with respect to t∈[a−h,b],λ∈J,t\in[a-h,b],\ \lambda\in J, to ((x12nz12n),(u13nu24n))∈FD\left(\binom{x_{12}^{n}}{z_{12}^{n}},\binom{u_{13}^{n}}{u_{24}^{n}}\right)\in F_{D}, for all (x120z120),(u130u240)∈X\binom{x_{12}^{0}}{z_{12}^{0}},\ \binom{u_{13}^{0}}{u_{24}^{0}}\in X.

If we take (x120z120)=(00)\binom{x_{12}^{0}}{z_{12}^{0}}=\binom{0}{0} and (u130u240)=(∂x120∂λ∂z120∂λ)=(00)\binom{u_{13}^{0}}{u_{24}^{0}}=\binom{\frac{\partial x_{12}^{0}}{\partial\lambda}}{\frac{\partial z_{12}^{0}}{\partial\lambda}}=\binom{0}{0} then (u131u241)=(∂x121∂λ∂z121∂λ)\binom{u_{13}^{1}}{u_{24}^{1}}=\binom{\frac{\partial x_{12}^{1}}{\partial\lambda}}{\frac{\partial z_{12}^{1}}{\partial\lambda}}.

By induction we prove that

(u13nu24n)=(∂x12n∂λ∂z12n∂λ),∀n∈ℕ.\binom{u_{13}^{n}}{u_{24}^{n}}=\binom{\frac{\partial x_{12}^{n}}{\partial\lambda}}{\frac{\partial z_{12}^{n}}{\partial\lambda}},\;\forall n\in\mathbb{N}.

So, (x12nz12n)​→u​n​i​f​(x12∗z12∗), as ​n→∞​and​(∂x12n∂λ∂z12n∂λ)​→u​n​i​f​(u13∗u24∗), as ​n→∞\binom{x_{12}^{n}}{z_{12}^{n}}\overset{unif}{\rightarrow}\binom{x_{12}^{\ast}}{z_{12}^{\ast}},\text{ as }n\rightarrow\infty\ \text{and}\ \binom{\frac{\partial x_{12}^{n}}{\partial\lambda}}{\frac{\partial z_{12}^{n}}{\partial\lambda}}\overset{unif}{\rightarrow}\binom{u_{13}^{\ast}}{u_{24}^{\ast}},\text{ as }n\rightarrow\infty. From a Weierstrass argument we get that there exists (∂x12∗∂λ∂z12∗∂λ),i=1,2\dbinom{\tfrac{\partial x_{12}^{\ast}}{\partial\lambda}}{\tfrac{\partial z_{12}^{\ast}}{\partial\lambda}},\ i=1,2 and(∂x12∗∂λ∂z12∗∂λ)=(u13∗u24∗)​.\dbinom{\tfrac{\partial x_{12}^{\ast}}{\partial\lambda}}{\tfrac{\partial z_{12}^{\ast}}{\partial\lambda}}=\dbinom{u_{13}^{\ast}}{u_{24}^{\ast}}\text{.}

∎

3.6. Ulam-Hyers stability

We start this section by presenting the Ulam-Hyers stability concept (see [16], [17]). For f∈C​([a,b]×ℝ4,ℝ)f\in C([a,b]\times\mathbb{R}^{4},\mathbb{R}), ε>0\varepsilon>0 and ψ∈C​([a−h,b],ℝ+),h>0,\psi\in C([a-h,b],\mathbb{R}_{+}),\ h>0, we consider the system

(3.7) {x′​(t)=z​(t),t∈[a,b]z′​(t)=f​(t,x​(t),z​(t),x​(t−h),z​(t−h)),t∈[a,b]\left\{\begin{array}[c]{l}x^{\prime}(t)=z(t),\ t\in[a,b]\\ z^{\prime}(t)=f(t,x(t),z(t),x(t-h),z(t-h)),\ t\in[a,b]\end{array}\right.

and the following inequations

(3.8) {|x′​(t)−z​(t)|≤ε,t∈[a,b]|z′​(t)−f​(t,x​(t),z​(t),x​(t−h),z​(t−h))|≤ε,t∈[a,b],\left\{\begin{array}[c]{l}\left|x^{\prime}(t)-z(t)\right|\leq\varepsilon,\ t\in[a,b]\\ \left|z^{\prime}(t)-f(t,x(t),z(t),x(t-h),z(t-h))\right|\leq\varepsilon,\ t\in[a,b],\end{array}\right.
(3.9) {|x′​(t)−z​(t)|≤ψ​(t),t∈[a,b]|z′​(t)−f​(t,x​(t),z​(t),x​(t−h),z​(t−h))|≤ψ​(t),t∈[a,b].\left\{\begin{array}[c]{l}\left|x^{\prime}(t)-z(t)\right|\leq\psi(t),\ t\in[a,b]\\ \left|z^{\prime}(t)-f(t,x(t),z(t),x(t-h),z(t-h))\right|\leq\psi(t),\ t\in[a,b].\end{array}\right.
Definition 3.6.

The system (3.7) is Ulam-Hyers stable if there exists a real number c>0c>0 such that for each ε>0\varepsilon>0 and for each solution (yw)∈C2​([a−h,b],ℝ2)\binom{y}{w}\in C^{2}([a-h,b],\mathbb{R}^{2}) of (3.8) there exists a solution (xz)∈C2​([a−h,b],ℝ2)\binom{x}{z}\in C^{2}([a-h,b],\mathbb{R}^{2}) of (3.7) with

|(yw)​(t)−(xz)​(t)|≤c​ε,∀t∈[a−h,b].\left|\binom{y}{w}(t)-\binom{x}{z}(t)\right|\leq c\varepsilon,\ \ \forall t\in[a-h,b].
Theorem 3.7.

We suppose that:

  • (i)

    the conditions (C1)-(C3) are satisfied;

  • (ii)

    Qn→0Q^{n}\rightarrow 0 as n→∞,n\rightarrow\infty, where Q=(b−a)​(01L1L2)Q=(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right).

Then the system (1.2) is Ulam-Hyers stable.

Proof.

The system (1.2) is equivalent with the functional integral system (1.5). We consider the operator E:C​([a−h,b],ℝ2)→C​([a−h,b],ℝ2),E:C([a-h,b],\mathbb{R}^{2})\rightarrow C([a-h,b],\mathbb{R}^{2}),\ defined by E​(xz)​(t):=E\binom{x}{z}(t):=the right hand side of (1.5), for t∈[a−h,b].t\in[a-h,b]. So

(xz)=E​(xz)​(t),t∈[a−h,b].\binom{x}{z}=E\binom{x}{z}(t),t\in[a-h,b].

From Theorem 3.1, EE is cc-WPO with c=[1−(b−a)​(01L1L2)]−1.c=\left[1-(b-a)\left(\begin{array}[c]{cc}0&1\\ L_{1}&L_{2}\end{array}\right)\right]^{-1}. Applying Theorem 2.7 we obtain that (1.2) is Ulam-Hyers stable. ∎

Remark 3.8.

Another proof for the above theorem can be done using Gronwall lemma ([7], [15]-[18]).

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2014

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