On a D.V. Ionescu’s problem for functional-differential equations of second order

Abstract

Abstract. The paper is devoted to the study of the following D.V. Ionescu’s problem
\[
\left \{
\begin{array}
[l]{l}%
-x_{1}^{\prime \prime}(t)=f_{1}(t,x_{1}%
(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t)),\ t\in \lbrack a,b]\newline \\
-x_{2}^{\prime \prime}(t)=f_{2}(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}%
(t),x_{2}^{\prime}(t))
\end{array}
\right.
\]
with polylocal conditions
\[
\left \{
\begin{array}
[c]{l}%
x_{1}(a)=x_{2}(b)=0\\
x_{1}(c)=x_{2}(c)\\
x_{1}^{\prime}(c)=x_{2}^{\prime}(c).
\end{array}
\right.
\]

Existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results of solution for the Cauchy problem are obtained using Perov fixed point theorem and weakly Picard operator theory.

Authors

Veronica Ana IIea
Babes-Bolyai University Kogalniceanu, 1, Cluj-Napoca, Romania

Diana Otrocol
Tiberiu Popoviciu Institute of Numerical Analysis

Keywords

Perov fixed point theorem; weakly Picard operators; polylocal problem; fixed points; data dependence.

Paper coordinates

V.A. Ilea, D. Otrocol, On a D.V. Ionescu’s problem for functional-differential equations of second order, Proceedings of the 10th IC-FPTA, July 9-18, 2012, Cluj-Napoca,  Romania, pp. 131-142, http://www.math.ubbcluj.ro/∼fptac

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Proceedings of the 10th IC-FPTA, July 9-18, 2012, Cluj-Napoca, Romania.

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ON A D.V. IONESCU’S PROBLEM FOR FUNCTIONAL-DIFFERENTIAL EQUATIONS OF SECOND ORDER

VERONICA ANA ILEA* AND DIANA OTROCOL**
*Babeş-Bolyai University
Kogălniceanu, 1, Cluj-Napoca, Romania
E-mail: vdarzu@math.ubbcluj.ro
**"T. Popoviciu" Institute of Numerical Analysis, P.O.Box. 68-1
400110, Cluj-Napoca, Romania
E-mail: dotrocol@ictp.acad.ro
Abstract

The paper is devoted to the study of the following D.V. Ionescu’s problem

{x1′′(t)=f1(t,x1(t),x2(t),x1(t),x2(t)),t[a,b]x2′′(t)=f2(t,x1(t),x2(t),x1(t),x2(t))\left\{\begin{array}[]{l}-x_{1}^{\prime\prime}(t)=f_{1}\left(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t)\right),t\in[a,b]\\ -x_{2}^{\prime\prime}(t)=f_{2}\left(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t)\right)\end{array}\right.

with polylocal conditions

{x1(a)=x2(b)=0x1(c)=x2(c)x1(c)=x2(c)\left\{\begin{array}[]{l}x_{1}(a)=x_{2}(b)=0\\ x_{1}(c)=x_{2}(c)\\ x_{1}^{\prime}(c)=x_{2}^{\prime}(c)\end{array}\right.

Existence, uniqueness and data dependence (monotony, continuity, differentiability with respect to parameter) results of solution for the Cauchy problem are obtained using Perov fixed point theorem and weakly Picard operator theory. Key Words and Phrases: Perov fixed point theorem, weakly Picard operators, polylocal problem, fixed points, data dependence. 2010 Mathematics Subject Classification: 47H10, 34K40.

1. Introduction

Let there be given real numbers a<c<ba<c<b and two functions f1,f2:[a,b]×4f_{1},f_{2}:[a,b]\times\mathbb{R}^{4}\rightarrow\mathbb{R}. We consider the boundary value problem for the system of functional-differential equations

{x1′′(t)=f1(t,x1(t),x2(t),x1(t),x2(t)),t[a,b]x2′′(t)=f2(t,x1(t),x2(t),x1(t),x2(t))\left\{\begin{array}[]{l}-x_{1}^{\prime\prime}(t)=f_{1}\left(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t)\right),t\in[a,b]\\ -x_{2}^{\prime\prime}(t)=f_{2}\left(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t)\right)\end{array}\right.

with polylocal conditions

{x1(a)=x2(b)=0x1(c)=x2(c)x1(c)=x2(c)\left\{\begin{array}[]{l}x_{1}(a)=x_{2}(b)=0\\ x_{1}(c)=x_{2}(c)\\ x_{1}^{\prime}(c)=x_{2}^{\prime}(c)\end{array}\right.

Boundary value problems that arise from different areas of applied mathematics and physics have received a lot of attention in the literature in the last decades (see for example [2], [3], [5], [6], [7] and references therein). In [9], D.V. Ionescu study the problem (1.1)-(1.2) using the successive approximation method. Several results of D.V. Ionescu have been cited and extended by: O Aramă [1], Gh. Coman [4], V. Ilea and D. Otrocol [8], G. Micula [10], A. Petrusel and I.A. Rus [12], etc. Our approach is based on the Perov fixed point theorem [11] and weakly Picard operator theory [15]-[17] in the following conditions
(C1)f1,f2C1([a,b]×4,);\left(\mathrm{C}_{1}\right)f_{1},f_{2}\in C^{1}\left([a,b]\times\mathbb{R}^{4},\mathbb{R}\right);
(C2)\left(\mathrm{C}_{2}\right) there exists Li>0L_{i}>0 such that

|fi(t,u1,u2,u3,u4)fi(t,v1,v2,v3,v4)|Lij=14|ujvj|\left|f_{i}\left(t,u_{1},u_{2},u_{3},u_{4}\right)-f_{i}\left(t,v_{1},v_{2},v_{3},v_{4}\right)\right|\leq L_{i}\sum_{j=1}^{4}\left|u_{j}-v_{j}\right|

for all t[a,b],uj,vj,i=1,2,j=1,4¯t\in[a,b],u_{j},v_{j}\in\mathbb{R},i=1,2,j=\overline{1,4}.

2. Ionescu’s problem in the linear case

In this section we study the existence and uniqueness theorem for the problem

{x1′′(t)=χ1(t),t[a,b]x2′′(t)=χ2(t)\displaystyle\left\{\begin{array}[]{l}-x_{1}^{\prime\prime}(t)=\chi_{1}(t),t\in[a,b]\\ -x_{2}^{\prime\prime}(t)=\chi_{2}(t)\end{array}\right. (2.1)
{x1(a)=x2(b)=0x1(c)=x2(c)x1(c)=x2(c)\displaystyle\left\{\begin{array}[]{l}x_{1}(a)=x_{2}(b)=0\\ x_{1}(c)=x_{2}(c)\\ x_{1}^{\prime}(c)=x_{2}^{\prime}(c)\end{array}\right. (2.2)

where χi:[a,b],i=1,2\chi_{i}:[a,b]\rightarrow\mathbb{R},i=1,2.
Theorem 2.1. We suppose that χiC([a,b],),i=1,2\chi_{i}\in C([a,b],\mathbb{R}),i=1,2. Then the problem (2.1)-(2.2) has a unique solution x=(x11,x22)C1([a,b],2)\stackrel{{\scriptstyle*}}=\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}}\right)\in C^{1}\left([a,b],\mathbb{R}^{2}\right) and

(x1(t)x2(t))=ab𝐆(t,s)(χ1(s)χ2(s))𝑑s\binom{x_{1}^{*}(t)}{x_{2}^{*}(t)}=\int_{a}^{b}\mathbf{G}(t,s)\binom{\chi_{1}(s)}{\chi_{2}(s)}ds

where 𝐆(t,s)\mathbf{G}(t,s) is the Green function of the problem

{x2′′(t)=χ1(t)x2′′(t)=χ2(t)x1(a)=x2(b)=0x1(c)=x2(c)x1(c)=x2(c)\left\{\begin{array}[]{l}-x_{2}^{\prime\prime}(t)=\chi_{1}(t)\\ -x_{2}^{\prime\prime}(t)=\chi_{2}(t)\\ x_{1}(a)=x_{2}(b)=0\\ x_{1}(c)=x_{2}(c)\\ x_{1}^{\prime}(c)=x_{2}^{\prime}(c)\end{array}\right.

𝐆(t,s)\mathbf{G}(t,s) has the following form

𝐆(t,s)=(G1(t,s)00G2(t,s))\mathbf{G}(t,s)=\left(\begin{array}[]{cc}G_{1}(t,s)&0\\ 0&G_{2}(t,s)\end{array}\right)

where for t(a,c)t\in(a,c)

G1(t,s)=((sa)(bt)ba0(ta)(bs)ba00(ta)(bs)ba)\displaystyle G_{1}(t,s)=\left(\begin{array}[]{cc}\frac{(s-a)(b-t)}{b-a}&0\\ \frac{(t-a)(b-s)}{b-a}&0\\ 0&\frac{(t-a)(b-s)}{b-a}\end{array}\right)
G2(t,s)=((sa)(bt)ba0(sa)(bt)bats0(ta)(bs)ba)\displaystyle G_{2}(t,s)=\left(\begin{array}[]{cc}\frac{(s-a)(b-t)}{b-a}&0\\ \frac{(s-a)(b-t)}{b-a}&t-s\\ 0&\frac{(t-a)(b-s)}{b-a}\end{array}\right)

and for t(c,b)t\in(c,b)

G1(t,s)=((sa)(bt)ba0st(ta)(bs)ba0(ta)(bs)ba)\displaystyle G_{1}(t,s)=\left(\begin{array}[]{cc}\frac{(s-a)(b-t)}{b-a}&0\\ s-t&\frac{(t-a)(b-s)}{b-a}\\ 0&\frac{(t-a)(b-s)}{b-a}\end{array}\right)
G2(t,s)=((sa)(bt)ba00(sa)(bt)ba0(ta)(bs)ba)\displaystyle G_{2}(t,s)=\left(\begin{array}[]{cc}\frac{(s-a)(b-t)}{b-a}&0\\ 0&\frac{(s-a)(b-t)}{b-a}\\ 0&\frac{(t-a)(b-s)}{b-a}\end{array}\right)

From Theorem 2.1 it follows that the problem (1.1)-(1.2) is equivalent with the system

(x1(t)x2(t))=ab𝐆(t,s)(f1(s,x1(s),x2(s),x1(s),x2(s))f2(s,x1(s),x2(s),x1(s),x2(s)))𝑑s\binom{-x_{1}(t)}{-x_{2}(t)}=\int_{a}^{b}\mathbf{G}(t,s)\binom{f_{1}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)}{f_{2}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)}ds (2.3)

In order to study the system (2.3), we shall use the weakly Picard operator technique. In the next section we present some notions and results from this theory.

3. Picard and weakly Picard operators

In this section, we introduce notation, definitions, and preliminary facts which are used throughout this paper (see [15]-[17]). Let ( X,dX,d ) be a metric space and A:XXA:X\rightarrow X an operator. We shall use the following notations:
FA:={xXA(x)=x}F_{A}:=\{x\in X\mid A(x)=x\} - the fixed point set of A;A;
I(A):={YXA(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:=AAn,A0=1X,A1=A,nA^{n+1}:=A\circ A^{n},A^{0}=1_{X},A^{1}=A,n\in\mathbb{N}.
Definition 3.1. Let ( X,dX,d ) be a metric space. An operator A:XXA:X\rightarrow X is a Picard operator (PO)(\mathrm{PO}) if there exists xXx^{*}\in X such that:
(i) FA={x}F_{A}=\left\{x^{*}\right\};
(ii) the sequence (An(x0))n\left(A^{n}\left(x_{0}\right)\right)_{n\in\mathbb{N}} converges to xx^{*} for all x0Xx_{0}\in X.

Definition 3.2. Let ( X,dX,d ) be a metric space. An operator A:XXA:X\rightarrow X is a weakly Picard operator (WPO) if the sequence (An(x))n\left(A^{n}(x)\right)_{n\in\mathbb{N}} converges for all xXx\in X, and its limit (which may depend on xx ) is a fixed point of AA.

Throughout this paper we denote by Mmm(+)M_{mm}\left(\mathbb{R}_{+}\right)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 Qk0Q^{k}\rightarrow 0 as kk\rightarrow\infty. It is known that the property of being convergent to zero is equivalent to each of the following three conditions (see [13], [14]):
(a) IQI-Q is nonsingular and (IQ)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 unit disc of the complex plane;
(c) IQI-Q is nonsingular and (IQ)1(I-Q)^{-1} has nonnegative elements.

We finish this section by recalling the following fundamental result
Theorem 3.3. (Perov’s fixed point theorem). Let (X,d)(X,d) with d(x,y)md(x,y)\in\mathbb{R}^{m}, be a complete generalized metric space and A:XXA:X\rightarrow X an operator. We suppose that there exists a matrix QMmm(+)Q\in M_{mm}\left(\mathbb{R}_{+}\right), such that
(i) d(A(x),A(y))Qd(x,y)d(A(x),A(y))\leq Qd(x,y), for all x,yXx,y\in X;
(ii) Qn0Q^{n}\rightarrow 0 as nn\rightarrow\infty.

Then
(a) FA={x}F_{A}=\left\{x^{*}\right\},
(b) An(x)=xA^{n}(x)=x^{*} as nn\rightarrow\infty and

d(An(x),x)(IQ)1Qnd(x0,A(x0))d\left(A^{n}(x),x^{*}\right)\leq(I-Q)^{-1}Q^{n}d\left(x_{0},A\left(x_{0}\right)\right)

4. Existence and uniqueness

In this section we use Perov’s fixed point theorem to obtain existence and uniqueness theorem for the solution of the problem (1.1)-(1.2).

We consider the Banach space X=(C1([a,b],2),C1)X=\left(C^{1}\left([a,b],\mathbb{R}^{2}\right),\|\cdot\|_{C^{1}}\right) where C1\|\cdot\|_{C^{1}}, is the Chebyshev norm defined by

(x1,x2)(y1,y2)C1:=(x1,x2)(y1,y2)+(x1,x2)(y1,y2)\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}:=\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{\infty}+\left\|\left(x_{1}^{\prime},x_{2}^{\prime}\right)-\left(y_{1}^{\prime},y_{2}^{\prime}\right)\right\|_{\infty}

and the operator A:XXA:X\rightarrow X defined by

A(x1,x2)(t)=(A1(x1,x2)(t)A2(x1,x2)(t)):=ab𝐆(t,s)(f1(s,x1(s),x2(s),x1(s),x2(s))f2(s,x1(s),x2(s),x1(s),x2(s)))𝑑s\begin{gathered}A\left(x_{1},x_{2}\right)(t)=\binom{A_{1}\left(x_{1},x_{2}\right)(t)}{A_{2}\left(x_{1},x_{2}\right)(t)}\\ :=\int_{a}^{b}\mathbf{G}(t,s)\binom{f_{1}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)}{f_{2}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)}ds\end{gathered}

We consider the problem (1.1)-(1.2) in the conditions (C1)\left(\mathrm{C}_{1}\right) and (C2)\left(\mathrm{C}_{2}\right). The problem (1.1)-(1.2) is equivalent with the fixed point equation

A(x1,x2)(t)=(x1,x2),xiC1([a,b],),i=1,2.A\left(x_{1},x_{2}\right)(t)=\left(x_{1},x_{2}\right),x_{i}\in C^{1}([a,b],\mathbb{R}),i=1,2.

For t[a,b]t\in[a,b] we have

|A1(x1,x2)(t)A1(y1,y2)(t)|=|ab𝐆(t,s)[f1(s,x1(s),x2(s),x1(s),x2(s))f1(s,y1(s),y2(s),y1(s),y2(s))]𝑑s|maxx[a,b]|abG1(t,s)𝑑s|L1((x1,x2)(y1,y2)+(x1,x2)(y1,y2))32(ba)2(1111)L1(x1,x2)(y1,y2)C1\begin{gathered}\left|A_{1}\left(x_{1},x_{2}\right)(t)-A_{1}\left(y_{1},y_{2}\right)(t)\right|\\ =\left|\int_{a}^{b}\mathbf{G}(t,s)\left[f_{1}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)-f_{1}\left(s,y_{1}(s),y_{2}(s),y_{1}^{\prime}(s),y_{2}^{\prime}(s)\right)\right]ds\right|\\ \leq\max_{x\in[a,b]}\left|\int_{a}^{b}G_{1}(t,s)ds\right|L_{1}\left(\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{\infty}+\left\|\left(x_{1}^{\prime},x_{2}^{\prime}\right)-\left(y_{1}^{\prime},y_{2}^{\prime}\right)\right\|_{\infty}\right)\\ \leq\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{cc}1&1\\ 1&1\end{array}\right)L_{1}\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}\end{gathered}

At the same time we have
A2(x1,x2)(t)A2(y1,y2)(t)32(ba)2(1111)L2(x1,x2)(y1,y2)C1\left\|A_{2}\left(x_{1},x_{2}\right)(t)-A_{2}\left(y_{1},y_{2}\right)(t)\right\|_{\infty}\leq\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{ll}1&1\\ 1&1\end{array}\right)L_{2}\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}.
For t[a,b]t\in[a,b] we have

|ddtA1(x1,x2)(t)ddtA1(y1,y2)(t)||abt𝐆(t,s)[f1(s,x1(s),x2(s),x1(s),x2(s))f1(s,y1(s),y2(s),y1(s),y2(s))]𝑑s||abt𝐆(t,s)𝑑s|L1((x1,x2)(y1,y2)+(x1,x2)(y1,y2))|abtG1(t,s)𝑑s|L1(x1,x2)(y1,y2)C1\begin{gathered}\left|\frac{d}{dt}A_{1}\left(x_{1},x_{2}\right)(t)-\frac{d}{dt}A_{1}\left(y_{1},y_{2}\right)(t)\right|\\ \leq\left|\int_{a}^{b}\frac{\partial}{\partial t}\mathbf{G}(t,s)\left[f_{1}\left(s,x_{1}(s),x_{2}(s),x_{1}^{\prime}(s),x_{2}^{\prime}(s)\right)-f_{1}\left(s,y_{1}(s),y_{2}(s),y_{1}^{\prime}(s),y_{2}^{\prime}(s)\right)\right]ds\right|\\ \leq\left|\int_{a}^{b}\frac{\partial}{\partial t}\mathbf{G}(t,s)ds\right|L_{1}\cdot\left(\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{\infty}+\left\|\left(x_{1}^{\prime},x_{2}^{\prime}\right)-\left(y_{1}^{\prime},y_{2}^{\prime}\right)\right\|_{\infty}\right)\\ \leq\left|\int_{a}^{b}\frac{\partial}{\partial t}G_{1}(t,s)ds\right|L_{1}\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}\end{gathered}
32(ba)(1101)L1(x1,x2)(y1,y2)C1.\leq\frac{3}{2}(b-a)\left(\begin{array}[]{cc}1&1\\ 0&1\end{array}\right)L_{1}\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}.

Analogous we have

ddtA2(x1,x2)(t)ddtA2(y1,y2)(t)32(ba)(1101)L2(x1,x2)(y1,y2)C1\begin{gathered}\left\|\frac{d}{dt}A_{2}\left(x_{1},x_{2}\right)(t)-\frac{d}{dt}A_{2}\left(y_{1},y_{2}\right)(t)\right\|_{\infty}\\ \leq\frac{3}{2}(b-a)\left(\begin{array}[]{cc}1&1\\ 0&1\end{array}\right)L_{2}\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}\end{gathered}

Then

(A1(x1,x2)(t)A1(y1,y2(t)C1A2(x1,x2)(t)A2(y1,y2(t)C1)(32(ba)2(L1L1L2L2)+32(ba)(L1L10L2))((x1,x2)(y1,y2)C1(x1,x2)(y1,y2)C1)\begin{gathered}\binom{\|A_{1}\left(x_{1},x_{2}\right)(t)-A_{1}\left(y_{1},y_{2}(t)\|_{C^{1}}\right.}{\|A_{2}\left(x_{1},x_{2}\right)(t)-A_{2}\left(y_{1},y_{2}(t)\|_{C^{1}}\right.}\\ \leq\left(\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{cc}L_{1}&L_{1}\\ L_{2}&L_{2}\end{array}\right)+\frac{3}{2}(b-a)\left(\begin{array}[]{cc}L_{1}&L_{1}\\ 0&L_{2}\end{array}\right)\right)\binom{\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}}{\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}}\end{gathered}

with Q:=(32(ba)2(L1L1L2L2)+32(ba)(L1L10L2))Q:=\left(\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{ll}L_{1}&L_{1}\\ L_{2}&L_{2}\end{array}\right)+\frac{3}{2}(b-a)\left(\begin{array}[]{cc}L_{1}&L_{1}\\ 0&L_{2}\end{array}\right)\right).
So, we have the following existence and uniqueness theorem
Theorem 4.1. We suppose that:
(i) the conditions ( C1C_{1} ) and ( C2C_{2} ) are satisfied;
(ii) Qn0Q^{n}\rightarrow 0 as nn\rightarrow\infty.

Then
(a) the problem (1.1)-(1.2) has a unique solution

x=(x11,x22)C1([a,b],2)\stackrel{{\scriptstyle*}}=\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}}\right)\in C^{1}\left([a,b],\mathbb{R}^{2}\right)

(b) for all (x10,x20)C1([a,b],2)\left(x_{1}^{0},x_{2}^{0}\right)\in C^{1}\left([a,b],\mathbb{R}^{2}\right), the sequence (x1n,x2n)n\left(x_{1}^{n},x_{2}^{n}\right)_{n\in\mathbb{N}} defined by

(x1n+1,x2n+1)=A(x1n,x2n)\left(x_{1}^{n+1},x_{2}^{n+1}\right)=A\left(x_{1}^{n},x_{2}^{n}\right)

converges uniformly to (x1,x2)\left(\stackrel{{\scriptstyle*}}_{1},\stackrel{{\scriptstyle*}}_{2}\right), for all t[a,b]t\in[a,b], and

(x1n,x2n)(x11,x22)C1(IQ)1Qn(x10,x20)(x11,x21)C1.\left\|\left(x_{1}^{n},x_{2}^{n}\right)-\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}}\right)\right\|_{C^{1}}\leq(I-Q)^{-1}Q^{n}\left\|\left(x_{1}^{0},x_{2}^{0}\right)-\left(x_{1}^{1},x_{2}^{1}\right)\right\|_{C^{1}}.

5. Data dependence: continuity

Consider the problem (1.1)-(1.2) with the dates f=(f1,f2),g=(g1,g2)f=\left(f_{1},f_{2}\right),g=\left(g_{1},g_{2}\right) and suppose that the conditions from Theorem 4.1 are satisfied.

Let f,gC2([a,b]×4,2)f,g\in C^{2}\left([a,b]\times\mathbb{R}^{4},\mathbb{R}^{2}\right). For simplicity we denote

Qf\displaystyle Q_{f} :=(32(ba)2(L1fL1fL2fL2f)+32(ba)(L1fL1f0L2f))\displaystyle:=\left(\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{cc}L_{1}^{f}&L_{1}^{f}\\ L_{2}^{f}&L_{2}^{f}\end{array}\right)+\frac{3}{2}(b-a)\left(\begin{array}[]{cc}L_{1}^{f}&L_{1}^{f}\\ 0&L_{2}^{f}\end{array}\right)\right) (5.1)
Qg\displaystyle Q_{g} :=(32(ba)2(L1gL1gL2gL2g)+32(ba)(L1gL1g0L2g))\displaystyle:=\left(\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{cc}L_{1}^{g}&L_{1}^{g}\\ L_{2}^{g}&L_{2}^{g}\end{array}\right)+\frac{3}{2}(b-a)\left(\begin{array}[]{cc}L_{1}^{g}&L_{1}^{g}\\ 0&L_{2}^{g}\end{array}\right)\right) (5.2)

and

Q:=max{Qf,Qg}Q:=\max\left\{Q_{f},Q_{g}\right\}

where max\max is taken w.r.t. the ordered relation of M22()M_{22}(\mathbb{R}).
Theorem 5.1. Let f=(f1,f2)f=\left(f_{1},f_{2}\right) and g=(g1,g2)g=\left(g_{1},g_{2}\right) satisfy the condition (C1)\left(C_{1}\right). Furthermore, we suppose that there exist η:=(η1,η2)+2\eta:=\left(\eta_{1},\eta_{2}\right)\in\mathbb{R}_{+}^{2}, such that

|fi(t,u1,u2,u3,u4)gi(t,u1,u2,u3,u4)|ηii=1,2,t[a,b],uj,j=1,4¯\begin{gathered}\left|f_{i}\left(t,u_{1},u_{2},u_{3},u_{4}\right)-g_{i}\left(t,u_{1},u_{2},u_{3},u_{4}\right)\right|\leq\eta_{i}\\ i=1,2,\forall t\in[a,b],u_{j}\in\mathbb{R},j=\overline{1,4}\end{gathered}

Then

x(t;f)x(t;g)C1(IQf)1η1\|\stackrel{{\scriptstyle*}}(t;f)-\stackrel{{\scriptstyle*}}(t;g)\|_{C^{1}}\leq\left(I-Q_{f}\right)^{-1}\eta_{1}

where x(t;f)\stackrel{{\scriptstyle*}}(t;f) and x(t;g)\stackrel{{\scriptstyle*}}(t;g) are the solution of the problem (1.1)-(1.2) with respect to ff and gg, with fi=(f1,f2),gi=(g1,g2)f_{i}=\left(f_{1},f_{2}\right),g_{i}=\left(g_{1},g_{2}\right).

Proof. Consider the operators AfA_{f} and AgA_{g}. From Theorem 4.1 it follows that Af(x1,x2)Ag(y1,y2)C1Q(x1,x2)(y1,y2)C1,(x1,x2),(y1,y2)X\left\|A_{f}\left(x_{1},x_{2}\right)-A_{g}\left(y_{1},y_{2}\right)\right\|_{C^{1}}\leq Q\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}},\left(x_{1},x_{2}\right),\left(y_{1},y_{2}\right)\in X.
We have now

xi(t;fi)xi(t;gi)C1=Afi(xi(t;fi))Agi(xi(t;gi))C1\displaystyle\left\|\stackrel{{\scriptstyle*}}_{i}\left(t;f_{i}\right)-\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right\|_{C^{1}}=\left\|A_{f_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;f_{i}\right)\right)-A_{g_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right)\right\|_{C^{1}}\leq
Afi(xi(t;fi))Afi(xi(t;gi))C1+Afi(xi(t;gi))Agi(xi(t;gi))C1\displaystyle\leq\left\|A_{f_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;f_{i}\right)\right)-A_{f_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right)\right\|_{C^{1}}+\left\|A_{f_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right)-A_{g_{i}}\left(\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right)\right\|_{C^{1}}\leq
Qfxi(t;fi)xi(t;gi)C1+ηi,i=1,2\displaystyle\leq Q_{f}\left\|\stackrel{{\scriptstyle*}}_{i}\left(t;f_{i}\right)-\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right\|_{C^{1}}+\eta_{i},i=1,2

Because Qn0Q^{n}\rightarrow 0 as nn\rightarrow\infty imply that

(IQ)1M22(2)(I-Q)^{-1}\in M_{22}\left(\mathbb{R}^{2}\right)

so we have

xi(t;fi)xi(t;gi)C1(IQf)1ηi\left\|\stackrel{{\scriptstyle*}}_{i}\left(t;f_{i}\right)-\stackrel{{\scriptstyle*}}_{i}\left(t;g_{i}\right)\right\|_{C^{1}}\leq\left(I-Q_{f}\right)^{-1}\eta_{i}

6. Data dependence: differentiability

In this section we present the dependence by parameter λ\lambda of the solution of the problem (1.1)-(1.2).

We shall use the following theorem
Theorem 6.1. (Fibre contraction principle). Let ( X,dX,d ) and ( Y,ρY,\rho ) be two metric spaces and A:X×YX×Y,A=(B,C),(B:XX,C:X×YYA: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
(i) ( Y,ρY,\rho ) is a complete metric space;
(ii) the operator BB is Picard operator;
(iii) there exists l[0,1)l\in[0,1) such that C(x,):YYC(x,\cdot):Y\rightarrow Y is a l-contraction, for all xXx\in X;
(iv) if (x,y)FA\left(x^{*},y^{*}\right)\in F_{A}, then C(,y)C\left(\cdot,y^{*}\right) is continuous in xx^{*}.

Then the operator AA is Picard operator.
Consider the following differential system with parameter:

x′′(t)=f(t,x1(t),x2(t),x1(t),x2(t);λ),t[a,b]\displaystyle-x^{\prime\prime}(t)=f\left(t,x_{1}(t),x_{2}(t),x_{1}^{\prime}(t),x_{2}^{\prime}(t);\lambda\right),t\in[a,b] (6.1)
{x1(a)=x2(b)=0x1(c)=x2(c)x1(c)=x2(c)\displaystyle\left\{\begin{array}[]{l}x_{1}(a)=x_{2}(b)=0\\ x_{1}(c)=x_{2}(c)\\ x_{1}^{\prime}(c)=x_{2}^{\prime}(c)\end{array}\right. (6.2)

where x=(x1,x2)x=\left(x_{1},x_{2}\right) and f=(f1,f2)f=\left(f_{1},f_{2}\right).
We suppose that
( C1\mathrm{C}_{1} ) a,b,c(a,b)a,b\in\mathbb{R},c\in(a,b) given, λJ\lambda\in J\subset\mathbb{R} a compact interval;
(C2)f=(f1,f2)C2([a,b]×4×J,2);\left(\mathrm{C}_{2}\right)f=\left(f_{1},f_{2}\right)\in C^{2}\left([a,b]\times\mathbb{R}^{4}\times J,\mathbb{R}^{2}\right);
(C3)\left(\mathrm{C}_{3}\right) there exists Li>0L_{i}>0 such that

(|fi(t,u1,u2,u3,u4;λ)uj|)i=1,2j=1,4¯Li\left(\left|\frac{\partial f_{i}\left(t,u_{1},u_{2},u_{3},u_{4};\lambda\right)}{\partial u_{j}}\right|\right)_{\begin{subarray}{c}i=1,2\\ j=\overline{1,4}\end{subarray}}\leq L_{i}

for all t[a,b],uj,i=1,2,j=1,4¯t\in[a,b],u_{j}\in\mathbb{R},i=1,2,j=\overline{1,4};
(C4)\left(\mathrm{C}_{4}\right) for Q=max{Qf,Qg}Q=\max\left\{Q_{f},Q_{g}\right\} with

Qf:=(32(ba)2(L1fL1fL2fL2f)+32(ba)(L1fL1f0L2f))Q_{f}:=\left(\frac{3}{2}(b-a)^{2}\left(\begin{array}[]{cc}L_{1}^{f}&L_{1}^{f}\\ L_{2}^{f}&L_{2}^{f}\end{array}\right)+\frac{3}{2}(b-a)\left(\begin{array}[]{cc}L_{1}^{f}&L_{1}^{f}\\ 0&L_{2}^{f}\end{array}\right)\right)

and QgQ_{g} analogous, we have Qn0Q^{n}\rightarrow 0 as nn\rightarrow\infty.
In the above conditions, from Theorem 4.1 we have that the problem (1.1)(1.2) has a unique solution, x(;λ)=(x11(;λ),x22(;λ))\stackrel{{\scriptstyle*}}(\cdot;\lambda)=\left(\stackrel{{\scriptstyle*}}{{x_{1}}}(\cdot;\lambda),\stackrel{{\scriptstyle*}}{{x_{2}}}(\cdot;\lambda)\right), for any λ\lambda\in\mathbb{R}. In what follows we shall prove that x(t;)C2(J,2)\stackrel{{\scriptstyle*}}(t;\cdot)\in C^{2}\left(J,\mathbb{R}^{2}\right), for all t[a,b]t\in[a,b].

For this we consider the system

x′′(t)=f(t,x1(t;λ),x2(t;λ),x1(t;λ),x2(t;λ);λ)-x^{\prime\prime}(t)=f\left(t,x_{1}(t;\lambda),x_{2}(t;\lambda),x_{1}^{\prime}(t;\lambda),x_{2}^{\prime}(t;\lambda);\lambda\right) (6.3)

for all t[a,b],λJ,x=(x1,x2)C1([a,b]×J,2),f=(f1,f2)t\in[a,b],\lambda\in J,x=\left(x_{1},x_{2}\right)\in C^{1}\left([a,b]\times J,\mathbb{R}^{2}\right),f=\left(f_{1},f_{2}\right).
The system (6.3) is equivalent with

(x1(t)x2(t))=ab𝐆(t,s)(f1(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)f2(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ))𝑑s\binom{-x_{1}(t)}{-x_{2}(t)}=\int_{a}^{b}\mathbf{G}(t,s)\binom{f_{1}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{f_{2}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}ds (6.4)

Let X:=(C1([a,b]×J,2),C1)X:=\left(C^{1}\left([a,b]\times J,\mathbb{R}^{2}\right),\|\cdot\|_{C^{1}}\right) with the Chebyshev norm

(x1,x2)(y1,y2)C1:=(x1,x2)(y1,y2)+(x1,x2)(y1,y2)\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{C^{1}}:=\left\|\left(x_{1},x_{2}\right)-\left(y_{1},y_{2}\right)\right\|_{\infty}+\left\|\left(x_{1}^{\prime},x_{2}^{\prime}\right)-\left(y_{1}^{\prime},y_{2}^{\prime}\right)\right\|_{\infty}

Now we consider the operator B:C1([a,b]×J,2)C1([a,b]×J,2)B:C^{1}\left([a,b]\times J,\mathbb{R}^{2}\right)\rightarrow C^{1}\left([a,b]\times J,\mathbb{R}^{2}\right) where

B(x1,x2)(t;λ)=(B1(x1,x2)(t;λ)B2(x1,x2)(t;λ)):= second part of (6.4). B\left(x_{1},x_{2}\right)(t;\lambda)=\binom{B_{1}\left(x_{1},x_{2}\right)(t;\lambda)}{B_{2}\left(x_{1},x_{2}\right)(t;\lambda)}:=\text{ second part of (6.4). }

It is clear, from the proof of the Theorem 4.1, that in the conditions ( C1\mathrm{C}_{1} )(C4)\left(\mathrm{C}_{4}\right), the operator BB is Picard operator, since

B(y1,y2)B(z1,z2)C1Q(y1,y2)(z1,z2)C1(y1,y2),(z1,z2)C1([a,b]×J,2)\begin{gathered}\left\|B\left(y_{1},y_{2}\right)-B\left(z_{1},z_{2}\right)\right\|_{C^{1}}\leq Q\left\|\left(y_{1},y_{2}\right)-\left(z_{1},z_{2}\right)\right\|_{C^{1}}\\ \forall\left(y_{1},y_{2}\right),\left(z_{1},z_{2}\right)\in C^{1}\left([a,b]\times J,\mathbb{R}^{2}\right)\end{gathered}

Let x=(x11,x22)\stackrel{{\scriptstyle*}}=\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}}\right) be the unique fixed point of BB.
We suppose that there exists i𝓍λ,i=1,2\frac{\partial\stackrel{{\scriptstyle\mathcal{x}}}^{*}}{\partial\lambda},i=1,2. From condition ( C3\mathrm{C}_{3} ) we have

xi(t;λ)λ=ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u1x1(s;λ)λ𝑑s\displaystyle\frac{\partial\stackrel{{\scriptstyle*}}_{i}^{*}(t;\lambda)}{\partial\lambda}=\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{1}}\cdot\frac{\partial\stackrel{{\scriptstyle*}}_{1}^{*}(s;\lambda)}{\partial\lambda}ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u2x2(s;λ)λ𝑑s\displaystyle\quad+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{2}}\cdot\frac{\partial\stackrel{{\scriptstyle*}}_{2}(s;\lambda)}{\partial\lambda}ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u3x1(s;λ)λ𝑑s\displaystyle\quad+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{3}}\cdot\frac{\partial\stackrel{{\scriptstyle*}}_{1}^{\prime}(s;\lambda)}{\partial\lambda}ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u4x22(s;λ)λ𝑑s\displaystyle\quad+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{4}}\cdot\frac{\partial{\stackrel{{\scriptstyle*}}{{x_{2}}}}^{\prime}(s;\lambda)}{\partial\lambda}ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)λ𝑑s\displaystyle\quad+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial\lambda}ds

for t[a,b],λJ,i=1,2t\in[a,b],\lambda\in J,i=1,2.
This relation suggest us to consider the following operator

C:X×XX,(x1,x2,y1,y2)C(x1,x2,y1,y2)C:X\times X\rightarrow X,\left(x_{1},x_{2},y_{1},y_{2}\right)\rightarrow C\left(x_{1},x_{2},y_{1},y_{2}\right)

defined by

C(x1,x2,y1,y2)(t;λ):=\displaystyle C\left(x_{1},x_{2},y_{1},y_{2}\right)(t;\lambda)=
=ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u1y1(s;λ)𝑑s\displaystyle=\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{1}}\cdot y_{1}(s;\lambda)ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u2y2(s;λ)𝑑s\displaystyle+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{2}}\cdot y_{2}(s;\lambda)ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u3y1(s;λ)𝑑s\displaystyle+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{3}}\cdot y_{1}^{\prime}(s;\lambda)ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)u4y2(s;λ)𝑑s\displaystyle+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial u_{4}}\cdot y_{2}^{\prime}(s;\lambda)ds
+ab𝐆(t,s)fi(s,x1(s;λ),x2(s;λ),x1(s;λ),x2(s;λ);λ)λ𝑑s\displaystyle+\int_{a}^{b}\mathbf{G}(t,s)\frac{\partial f_{i}\left(s,x_{1}(s;\lambda),x_{2}(s;\lambda),x_{1}^{\prime}(s;\lambda),x_{2}^{\prime}(s;\lambda);\lambda\right)}{\partial\lambda}ds

where yi(t;λ):=xi(t;λ)λy_{i}(t;\lambda):=\frac{\partial x_{i}(t;\lambda)}{\partial\lambda} and yi(t;λ):=xi(t;λ)λy_{i}^{\prime}(t;\lambda):=\frac{\partial x_{i}^{\prime}(t;\lambda)}{\partial\lambda} for t[a,b],λJ,i=1,2t\in[a,b],\lambda\in J,i=1,2. In this way we have the triangular operator

A:X×XX×XA(x1,x2,y1,y2)=(B(x1,x2)(t;λ),C(x1,x2,y1,y2)(t;λ))\begin{gathered}A:X\times X\rightarrow X\times X\\ A\left(x_{1},x_{2},y_{1},y_{2}\right)=\left(B\left(x_{1},x_{2}\right)(t;\lambda),C\left(x_{1},x_{2},y_{1},y_{2}\right)(t;\lambda)\right)\end{gathered}

where BB is a Picard operator and C(x1,x2,,):XXC\left(x_{1},x_{2},\cdot,\cdot\right):X\rightarrow X is QQ-contraction. Indeed we have

C(x1,x2,u1,u2)(t;λ)C(x1,x22,v1,v2)(t;λ)C1Q(u1,u2)(v1,v2)C1,u=(u1,u2),v=(v1,v2)X,t[a,b],λJ\begin{gathered}\left\|C\left(x_{1}^{*},\stackrel{{\scriptstyle*}}_{2},u_{1},u_{2}\right)(t;\lambda)-C\left(\stackrel{{\scriptstyle*}}_{1},\stackrel{{\scriptstyle*}}{{x_{2}}},v_{1},v_{2}\right)(t;\lambda)\right\|_{C^{1}}\leq Q\left\|\left(u_{1},u_{2}\right)-\left(v_{1},v_{2}\right)\right\|_{C^{1}},\\ \forall u=\left(u_{1},u_{2}\right),v=\left(v_{1},v_{2}\right)\in X,t\in[a,b],\lambda\in J\end{gathered}

Since Qn0Q^{n}\rightarrow 0 as nn\rightarrow\infty, from the theorem of fibre contraction (see [15]) follows that the operator AA is Picard operator and has a unique fixed point (x11,x22,y11,y22)X×X\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}},\stackrel{{\scriptstyle*}}{{y_{1}}},\stackrel{{\scriptstyle*}}{{y_{2}}}\right)\in X\times X. So the sequences

(x1n+1,x2n+1,y1n+1,y2n+1)=(B(x1n,x2n),C(x1n,x2n,y1n,y2n)),n\left(x_{1}^{n+1},x_{2}^{n+1},y_{1}^{n+1},y_{2}^{n+1}\right)=\left(B\left(x_{1}^{n},x_{2}^{n}\right),C\left(x_{1}^{n},x_{2}^{n},y_{1}^{n},y_{2}^{n}\right)\right),n\in\mathbb{N}

converges uniformly (with respect to t[a,b],λJt\in[a,b],\lambda\in J ) to (x11,x22,y11,y22)FA\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}},\stackrel{{\scriptstyle*}}{{y_{1}}},\stackrel{{\scriptstyle*}}{{y_{2}}}\right)\in F_{A}, for any (x10,x20),(y10,y20)X\left(x_{1}^{0},x_{2}^{0}\right),\left(y_{1}^{0},y_{2}^{0}\right)\in X. If we take

xi0=0,yi0=xi0λ=0, then yi1=xi1λ,i=1,2x_{i}^{0}=0,y_{i}^{0}=\frac{\partial x_{i}^{0}}{\partial\lambda}=0,\text{ then }y_{i}^{1}=\frac{\partial x_{i}^{1}}{\partial\lambda},i=1,2

By induction we prove that

yin=xinλ,n,i=1,2¯y_{i}^{n}=\frac{\partial x_{i}^{n}}{\partial\lambda},\forall n\in\mathbb{N},i=\overline{1,2}

Thus

xin unif xi, as n,i=1,2xinλ unif yii, as n,i=1,2¯\begin{gathered}x_{i}^{n}\xrightarrow{\text{ unif }}\stackrel{{\scriptstyle*}}_{i},\text{ as }n\rightarrow\infty,i=1,2\\ \frac{\partial x_{i}^{n}}{\partial\lambda}\xrightarrow{\text{ unif }}\stackrel{{\scriptstyle*}}{{y_{i}}},\text{ as }n\rightarrow\infty,i=\overline{1,2}\end{gathered}

These imply that there exists xiλ\frac{\partial\stackrel{{\scriptstyle*}}_{i}}{\partial\lambda} and

xi(t;λ)λ=yii(t;λ),i=1,2¯\frac{\partial x_{i}(t;\lambda)}{\partial\lambda}=\stackrel{{\scriptstyle*}}{{y_{i}}}(t;\lambda),i=\overline{1,2}

So, we have
Theorem 6.2. Suppose that conditions (C1)(C4)\left(\mathrm{C}_{1}\right)-\left(\mathrm{C}_{4}\right) hold. Then,
(i) the problem (1.1)-(1.2) has a unique solution

x=(x11,x22)C2([a,b]×J,2)\stackrel{{\scriptstyle*}}=\left(\stackrel{{\scriptstyle*}}{{x_{1}}},\stackrel{{\scriptstyle*}}{{x_{2}}}\right)\in C^{2}\left([a,b]\times J,\mathbb{R}^{2}\right)

(ii) x(t;)C1(J,2),t[a,b]\stackrel{{\scriptstyle*}}(t;\cdot)\in C^{1}\left(J,\mathbb{R}^{2}\right),\forall t\in[a,b].

Acknowledgement. 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.

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