Abstract

The aim of this paper is to study a differential equation with abstract Volterra operator. Existence and uniqueness, inequalities of Caplygin type and data dependence (monotony, continuity) results for the solution of the Cauchy problem are obtained using weakly Picard operators theory.

Authors

Diana Otrocol
Tiberiu Popoviciu Institute of Numerical Analysis, Romanian Academy

Diana Otrocol

Keywords

Data dependence, weakly Picard operators, abstract Volterra operators.

Paper coordinates

D. Otrocol, Abstract Volterra operators, Carpathian J. Math. 24 (2008) no. 3, 370-377

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Carpathian Journal of Mathematics

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North University Center at Baia Mare, Technical University of Cluj-Napoca (NUCBM), Romania

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1584 – 2851

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1843 – 4401

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[12] Rus, I. A., Weakly Picard operators and applications, Seminar on Fixed Point Theory, Cluj-Napoca, 2 (2001), 41–58

Abstract Volterra operators

Diana Otrocol “T. Popoviciu” Institute of Numerical Analysis
PO Box 68-1, 400110, Cluj-Napoca, Romania
dotrocol@ictp.acad.ro
Abstract.

The aim of this paper is to study a differential equation with abstract Volterra operator. Existence and uniqueness, inequalities of Čaplygin type and data dependence (monotony, continuity) results for the solution of the Cauchy problem are obtained using weakly Picard operators theory.

Key words and phrases:
Abstract Volterra operators, weakly Picard operators, data dependence.
2000 Mathematics Subject Classification:
34L05, 47H10.

1. Introduction

The equations involving abstract Volterra operators have been investigated since 1928 by many authors. We mention here the contributions made by L. Tonelli (1928), S. Cinquini (1930), D. Graffi (1930), A.N. Tychonoff (1938). The definition of abstract Volterra operator introduced by A.N. Tychonoff is very easy to grasp:

An operator is abstract Volterra operator if any two functions coinciding on an interval [a,t][a,t] have equal images on [a,t],t∈[a,b][a,t],t\in[a,b].

Such operators appear in many areas of investigation: control theory, continuum mechanics, engineering, dynamics of the nuclear reactors. Applications of such operators are contained in [2], [4], [5].

The Volterra equation with abstract operator are usually written in the form

x′​(t)=V​(x)​(t),t∈[a,b].x^{\prime}(t)=V(x)(t),\ t\in[a,b].

where VV stands for such an operator.

This functional equation have been investigated by many authors and results pertaining existence and uniqueness, continuous dependence of solution to the Cauchy’s problem and even more specialized topics can be found in [3], [6], [7], [9]. The fixed point method is certainly one of the most used to study the existence of solution, as well as other basic problems, related to the equation 1, see [1], [4], [7].

This paper has as main objective to provide existence and uniqueness, inequalities of Čaplygin type and data dependence (monotony, continuity) results for the solution of a differential equation with abstract Volterra operator using weakly Picard operators theory. As an illustration of the fact that weakly Picard operators theory can be used with success in case of abstract Volterra operator, we shall give some application of the theory presented below.

We consider the following Cauchy problem

(1) x′​(t)=f​(t,x​(t),V​(x)​(t)),t∈[a,b]x^{\prime}(t)=f(t,x(t),V(x)(t)),\ t\in[a,b]
(2) x​(a)=αx(a)=\alpha

where

  • (C1)

    α∈ℝ\alpha\in\mathbb{R}, f∈C​([a,b]×ℝ2,ℝ),V∈C​(C​[a,b],C​[a,b])f\in C([a,b]\times\mathbb{R}^{2},\mathbb{R}),\ V\in C(C[a,b],C[a,b]) are given;

  • (C2)

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

    |f​(t,u1,u2)−f​(t,v1,v2)|≤Lf​∑i=12|ui−vi|,\left|f(t,u_{1},u_{2})-f(t,v_{1},v_{2})\right|\leq L_{f}\sum_{i=1}^{2}\left|u_{i}-v_{i}\right|,

    ∀t∈[a,b],ui,vi∈ℝ,i=1,2\forall t\in[a,b],u_{i},v_{i}\in\mathbb{R},i=1,2;

  • (C3)

    there exists LV>0L_{V}>0 such that

    |V​(x)​(t)−V​(y)​(t)|≤LV​|x​(t)−y​(t)|,\left|V(x)(t)-V(y)(t)\right|\leq L_{V}\left|x(t)-y(t)\right|,

    ∀x,y∈C​[a,b],t∈[a,b]\forall x,y\in C[a,b],\ t\in[a,b].

In the condition (C1)(C_{1}), the problem (1)–(2), is equivalent with the fixed point equation

(3) x​(t)=α+∫atf​(s,x​(s),V​(x)​(s))​𝑑s,t∈[a,b],x∈C​[a,b]x(t)=\alpha+\int_{a}^{t}f(s,x(s),V(x)(s))ds,\ t\in[a,b],\ x\in C[a,b]

and the equation (1) is equivalent with

(4) x​(t)=x​(a)+∫atf​(s,x​(s),V​(x)​(s))​𝑑s,t∈[a,b],x∈C​[a,b].x(t)=x(a)+\int_{a}^{t}f(s,x(s),V(x)(s))ds,\ t\in[a,b],x\in C[a,b].

Let us consider the following operators Bf,Ef:C​[a,b]→C​[a,b]B_{f},E_{f}:C[a,b]\rightarrow C[a,b] defined by Bf​(x)​(t):=second part of (3)B_{f}(x)(t):=\text{second part of (\ref{ec3.aV1})} and Ef​(x)​(t):=second part of (4).E_{f}(x)(t):=\text{second part of (\ref{ec4.aV1}).} For α∈ℝ,\alpha\in\mathbb{R}, we consider Xα:={x∈C​[a,b]|x​(a)=α}.X_{\alpha}:=\{x\in C[a,b]|\ x(a)=\alpha\}. We remark that C​[a,b]=∪α∈ℝ​XαC[a,b]=\underset{\alpha\in\mathbb{R}}{\cup}X_{\alpha} is a partition of C​[a,b].C[a,b]. We have

Lemma 1.

If (C1)(C_{1}) is satisfied, then

  • (a)

    Bf​(C​[a,b])⊂XαB_{f}(C[a,b])\subset X_{\alpha} and Ef​(Xα)⊂Xα,∀α∈ℝ;E_{f}(X_{\alpha})\subset X_{\alpha},\ \forall\alpha\in\mathbb{R};

  • (b)

    Bf|Xα=Ef|Xα,∀α∈ℝ.B_{f}|_{X_{\alpha}}=E_{f}|_{X_{\alpha}},\ \forall\alpha\in\mathbb{R}.

For a better understanding of the weakly Picard operator theory, we shall present some notions and results from Rus [10]–[12].

2. Weakly Picard operators

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 point 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 subsets 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.

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:

  1. (i)

    FA={x∗};F_{A}=\{x^{\ast}\};

  2. (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.

Remark 3.

Accordingly to the definition, the contraction principle insures that, if A:X→XA:X\rightarrow X is an α\alpha -contraction on the complete metric space XX, then it is a Picard operator.

Definition 4.

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 5.

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 6.

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

Definition 7.

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.
Lemma 8.

Let (X,d,≤)(X,d,\leq) be an ordered metric space and A:X→XA:X\rightarrow X an operator. We suppose that:

  • (i)

    AA is WPO;

  • (ii)

    AA is increasing.

Then, the operator A∞A^{\infty} is increasing.

Lemma 9.

Let (X,d,≤)(X,d,\leq) an ordered metric space and A,B,C:X→XA,B,C:X\rightarrow X be such that:

(i)(i) the operator A,B,CA,B,C are WPOs;

(i​i)(ii) A≤B≤CA\leq B\leq C;

(i​i​i)(iii) the operator BB is increasing.

Then x≤y≤zx\leq y\leq z implies that A∞​(x)≤B∞​(y)≤C∞​(z)A^{\infty}(x)\leq B^{\infty}(y)\leq C^{\infty}(z).

For some examples of WPOs see [8], [11], [12].

3. Existence

Consider the problem (1)–(2) where V:C​[a,b]→[a,b],x→V​(x)V:C[a,b]\rightarrow[a,b],\ x\rightarrow V(x) and f∈C​([a,b]×J2),J⊂ℝf\in C([a,b]\times J^{2}),J\subset\mathbb{R} a compact interval. This problem is equivalent with the integral equation (3).

Let B¯(a,r)⊂(C[a,b],∥⋅∥C)\overline{B}(a,r)\subset(C[a,b],\left\|\cdot\right\|_{C}) and suppose that the compatibility condition between the sphere and the compact JJ hold, i.e.

y∈B¯​(a,r)​ imply that ​y​(x)∈J,∀x∈[a,b].y\in\overline{B}(a,r)\text{ imply that }y(x)\in J,\forall x\in[a,b].

We note

M=maxx∈[a,b]​|f​(x,u,v)|,u,v∈J.M=\underset{x\in[a,b]}{\max}\left|f(x,u,v)\right|,\ u,v\in J.

Then we have

Theorem 10.

We suppose:

  • (i)

    f∈C​([a,b]×J2),J⊂ℝf\in C([a,b]\times J^{2}),J\subset\mathbb{R} a compact interval;

  • (ii)

    V∈C​(C​[a,b],C​[a,b]);V\in C(C[a,b],C[a,b]);

  • (iii)

    y∈B¯​(a,r)y\in\overline{B}(a,r) imply that y​(x)∈J,∀x∈[a,b];y(x)\in J,\forall x\in[a,b];

  • (iv)

    M​(b−a)≤r.M(b-a)\leq r.

Then, the problem (1)–(2) has in B¯​(a,r)\overline{B}(a,r) at least one solution.

Proof.

We consider the operator A:B¯​(a,r)→C​[a,b],A:\overline{B}(a,r)\rightarrow C[a,b],

A​(x)​(t)=α+∫atf​(s,x​(s),V​(x)​(s))​𝑑s,t∈[a,b].A(x)(t)=\alpha+\int_{a}^{t}f(s,x(s),V(x)(s))ds,t\in[a,b].

We have A​(x)​(t)≤M​(b−a)≤rA(x)(t)\leq M(b-a)\leq r, so the condition (iv) assures the invariance of the sphere. From this we have A:B¯​(a,r)→B¯​(a,r)A:\overline{B}(a,r)\rightarrow\overline{B}(a,r).

The set B¯​(a,r)\overline{B}(a,r) is bounded, closed and convex in C​[a,b].C[a,b]. The operator AA is compact and continuous, so AA is complete continuous. A​(B¯​(a,r))A(\overline{B}(a,r)) is bounded and equicontinuous and from Arzela-Ascoli theorem we have that A​(B¯​(a,r))A(\overline{B}(a,r)) is relative compact. We apply Schauder fixed point theorem. ∎

4. Existence and uniqueness

In what follows we consider the problem (1)–(2) in the conditions (C1)–(C3).

Theorem 11.

We suppose that the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}) are satisfied. Then the problem (1)–(2) has in C​[a,b]C[a,b] a unique solution and this solution is the uniform limit of the successive approximations.

Proof.

The problem (1)–(2) is equivalent with the fixed point equation

Bf​(x)=x,x∈C​[a,b].B_{f}(x)=x,\ x\in C[a,b].

On the other hand we have that

|Bf​(x)​(t)−Bf​(y)​(t)|\displaystyle\left|B_{f}(x)(t)-B_{f}(y)(t)\right| ≤∫at|f​(s,x​(s),V​(x)​(s))−f​(s,y​(s),V​(y)​(s))|​𝑑s≤\displaystyle\leq\int_{a}^{t}\left|f(s,x(s),V(x)(s))-f(s,y(s),V(y)(s))\right|ds\leq
≤Lf​(∫at|x​(s)−y​(s)|​𝑑s+∫at|V​(x)​(t)−V​(y)​(t)|​𝑑s)\displaystyle\leq L_{f}(\int_{a}^{t}\left|x(s)-y(s)\right|ds+\int_{a}^{t}\left|V(x)(t)-V(y)(t)\right|ds)
≤Lf(∫at|x(s)−y(s)|e−τ​(s−a)eτ​(s−a)ds+\displaystyle\leq L_{f}(\int_{a}^{t}\left|x(s)-y(s)\right|e^{-\tau(s-a)}e^{\tau(s-a)}ds+
+∫at|V(x)(t)−V(y)(t)|e−τ​(s−a)eτ​(s−a)ds)\displaystyle\quad+\int_{a}^{t}\left|V(x)(t)-V(y)(t)\right|e^{-\tau(s-a)}e^{\tau(s-a)}ds)
≤eτ​tτ​(Lf+Lf​LV)​‖x−y‖B.\displaystyle\leq\frac{e^{\tau t}}{\tau}(L_{f}+L_{f}L_{V})\left\|x-y\right\|_{B}.

So,

‖Bf​(x)−Bf​(y)‖B≤1τ​Lf​(1+LV)​‖x−y‖B,∀x,y∈C​[a,b],\left\|B_{f}(x)-B_{f}(y)\right\|_{B}\leq\tfrac{1}{\tau}L_{f}(1+L_{V})\left\|x-y\right\|_{B},\ \forall x,y\in C[a,b],

i.e., BfB_{f} is a contraction w.r.t. Bielecki norm on C​[a,b]C[a,b]. The proof follows from the contraction principle. ∎

Remark 12.

In the conditions of Theorem 11, the operator BfB_{f} is PO. But

Bf|Xα=Ef|Xα,∀α∈ℝ.B_{f}|_{X_{\alpha}}=E_{f}|_{X_{\alpha}},\ \forall\alpha\in\mathbb{R}.

Hence, the operator EfE_{f} is WPO and FEf∩Xα={xα∗},∀α∈ℝ,F_{E_{f}}\cap X_{\alpha}=\{x_{\alpha}^{\ast}\},\forall\alpha\in\mathbb{R}, where xα∗x_{\alpha}^{\ast} is the unique solution of the problem (1)–(2).

5. Inequalities of Čaplygin type

In this section we shall study the relation between the solution of the problem (1)–(2) and the subsolution of the same problem. We have

Theorem 13.

We suppose that:

  • (a)

    the conditions (C1),(C2)(C_{1}),\ (C_{2}) and (C3)(C_{3}) are satisfied;

  • (b)

    f​(x,⋅,⋅):ℝ2→ℝ2f(x,\cdot,\cdot):\mathbb{R}^{2}\rightarrow\mathbb{R}^{2} is increasing;

  • (c)

    V:C​[a,b]→C​[a,b]V:C[a,b]\rightarrow C[a,b] is increasing.

Let xx be a solution of equation (1) and yy a solution of the inequality

y′​(t)≤f​(t,y​(t),V​(y)​(t)),t∈[a,b].y^{\prime}(t)\leq f(t,y(t),V(y)(t)),\ t\in[a,b].

Then y​(a)≤x​(a)​ implies that ​y≤xy(a)\leq x(a)\text{ implies that }y\leq x.

Proof.

In the terms of the operator Ef,E_{f}, we have

x=Ef​(x)​ and ​y≤Ef​(y),x=E_{f}(x)\text{ and }y\leq E_{f}(y),

and y​(a)≤x​(a).y(a)\leq x(a). From the conditions (C1),(C2)(C_{1}),\ (C_{2}) and (C3)(C_{3}) we have that the operator EfE_{f} is WPO. From the condition (b), Ef∞E_{f}^{\infty} is increasing (see [11]). If α∈ℝ,\alpha\in\mathbb{R}, then we denote by α~\widetilde{\alpha} the following function

α~:[a,b]→ℝ,α~​(t)=α,∀t∈[a,b].\widetilde{\alpha}:[a,b]\rightarrow\mathbb{R},\ \widetilde{\alpha}(t)=\alpha,\ \forall t\in[a,b].

We have

y≤Ef​(y)≤…≤Ef∞​(y)=Ef∞​(y~​(a))≤Ef∞​(x~​(a))=x.y\leq E_{f}(y)\leq\ldots\leq E_{f}^{\infty}(y)=E_{f}^{\infty}(\widetilde{y}(a))\leq E_{f}^{\infty}(\widetilde{x}(a))=x.

∎

6. Data dependence: monotony

In this section we study the monotony of the system (1)–(2) with respect to ff. For this we use Lemma 9.

Theorem 14.

We suppose that fi∈C​([a,b]×ℝ2,ℝ),i=1,2,f_{i}\in C([a,b]\times\mathbb{R}^{2},\mathbb{R}),i=1,2, satisfy the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}). Furthermore, we suppose that:

  • (i)

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

  • (ii)

    f2​(t,⋅,⋅):ℝ2→ℝ2f_{2}(t,\cdot,\cdot):\mathbb{R}^{2}\rightarrow\mathbb{R}^{2} is increasing;

  • (iii)

    V:C​[a,b]→C​[a,b]V:C[a,b]\rightarrow C[a,b] is increasing.

Let xi∈C1​[a,b]x_{i}\in C^{1}[a,b] be a solution of the equation

xi′​(t)=fi​(t,x​(t),V​(x)​(t)),t∈[a,b]​ and ​i=1,2,3.x_{i}^{\prime}(t)=f_{i}(t,x(t),V(x)(t)),\ t\in[a,b]\text{ and }i=1,2,3.

If, x1​(a)≤x2​(a)≤x3​(a)x_{1}(a)\leq x_{2}(a)\leq x_{3}(a), then x1≤x2≤x3.x_{1}\leq x_{2}\leq x_{3}.

Proof.

From Theorem 11 we have that the operator Efi,i=1,2,3,E_{f_{i}},i=1,2,3,\ are WPOs. From the condition (ii) the operator Ef2E_{f_{2}} is monotone increasing. From the condition (i) it follows that Ef1≤Ef2≤Ef3E_{f_{1}}\leq E_{f_{2}}\leq E_{f_{3}}.

Let x~i​(a)∈C​[a,b]\widetilde{x}_{i}(a)\in C[a,b] be defined by x~i​(a)​(t)=xi​(a),∀t∈[a,b]\widetilde{x}_{i}(a)(t)=x_{i}(a),\ \forall t\in[a,b]. It is clear that

x~1​(a)​(t)≤x~2​(a)​(t)≤x~3​(a)​(t),∀t∈[a,b].\widetilde{x}_{1}(a)(t)\leq\widetilde{x}_{2}(a)(t)\leq\widetilde{x}_{3}(a)(t),\ \forall t\in[a,b].

From Lemma 9 we have that

Ef1∞​(x~1​(a))≤Ef2∞​(x~2​(a))≤Ef3∞​(x~3​(a)).E_{f_{1}}^{\infty}(\widetilde{x}_{1}(a))\leq E_{f_{2}}^{\infty}(\widetilde{x}_{2}(a))\leq E_{f_{3}}^{\infty}(\widetilde{x}_{3}(a)).

But, xi=Ef​i∞​(x~i​(a)),x_{i}=E_{fi}^{\infty}(\widetilde{x}_{i}(a)), and x1≤x2≤x3.x_{1}\leq x_{2}\leq x_{3}. ∎

7. Data dependence: continuity

Consider the Cauchy problem (1)–(2) and suppose the conditions of the Theorem 11 are satisfied. Denote by x∗​(⋅;α,f),x^{\ast}(\cdot;\alpha,f),\ the solution of this problem. We shall use the data dependence theorem (see [11]).

Theorem 15.

We suppose that αi,fi,i=1,2\alpha_{i},f_{i},i=1,2 satisfy the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}). Furthermore, we suppose that there exists ηi>0,i=1,2\eta_{i}>0,i=1,2 such that

  1. (i)

    |α1​(t)−α2​(t)|≤η1,∀t∈[a,b];\left|\alpha_{1}(t)-\alpha_{2}(t)\right|\leq\eta_{1},\forall t\in[a,b];

  2. (ii)

    |f1​(t,u1,u2)−f2​(t,u1,u2)|≤η2,∀t∈[a,b],ui∈ℝ,i=1,2.\left|f_{1}(t,u_{1},u_{2})-f_{2}(t,u_{1},u_{2})\right|\leq\eta_{2},\forall t\in[a,b],u_{i}\in\mathbb{R},i=1,2.

Then

‖x1∗​(t;α1,f1)−x2∗​(t;α2,f2)‖≤η1+(b−a)​η21−1τ​Lf​(1+LV)​(b−a),\left\|x_{1}^{\ast}(t;\alpha_{1},f_{1})-x_{2}^{\ast}(t;\alpha_{2},f_{2})\right\|\leq\frac{\eta_{1}+(b-a)\eta_{2}}{1-\tfrac{1}{\tau}L_{f}(1+L_{V})(b-a)},

where xi∗​(t;αi,fi),i=1,2x_{i}^{\ast}(t;\alpha_{i},f_{i}),i=1,2 are the solution of the problem (1)–(2) with respect to αi,fi\alpha_{i},f_{i} and Lf=max⁡(Lf1,Lf2).L_{f}=\max(L_{f_{1}},L_{f_{2}}).

Proof.

Consider the operators Bαi,fi,i=1,2.B_{\alpha_{i},f_{i}},i=1,2. From Theorem 11 these operators are contractions. Additionally

‖Bα1,f1​(x)−Bα2,f2​(x)‖≤η1+(b−a)​η2,∀x∈C​[a,b]\left\|B_{\alpha_{1},f_{1}}(x)-B_{\alpha_{2},f_{2}}(x)\!\right\|\leq\eta_{1}+(b-a)\eta_{2},\forall x\in C[a,b]

Now the proof follows from the the data dependence theorem (see [11]). ∎

In what follows we shall use the cc-WPOs techniques to give some data dependence results.

Theorem 16.

[12] Let (X,d)(X,d) be a metric space and Ai:X→X,i=1,2.A_{i}:X\rightarrow X,\ i=1,2. Suppose that

  • (i)

    the operator AiA_{i} is cic_{i}-weakly Picard operator, i=1,2;i\!=\!1,2;

  • (ii)

    there exists η>0\eta>0 such that

    d​(A1​(x),A2​(x))≤η,∀x∈X.d(A_{1}(x),A_{2}(x))\leq\eta,\ \forall x\in X.

Then H​(FA1,FA2)≤η​max⁡(c1,c2).H(F_{A_{1}},F_{A_{2}})\leq\eta\max(c_{1},c_{2}).

We have

Theorem 17.

We suppose that f1f_{1} and f2f_{2} satisfy the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}). Let SEf1,SEf2S_{E_{f_{1}}},S_{E_{f_{2}}} be the solution set of system (1) corresponding to f1f_{1} and f2f_{2}. Suppose that there exists η>0,\eta>0, such that

(5) |f1​(t,u1,u2)−f2​(t,u1,u2)|≤η\left|f_{1}(t,u_{1},u_{2})-f_{2}(t,u_{1},u_{2})\right|\leq\eta

for all t∈[a,b],ui∈ℝ,i=1,2.t\in[a,b],u_{i}\in\mathbb{R},i=1,2. Then

H∥⋅∥C​(SEf1,SEf2)≤(b−a)​η1−1τ​Lf​(1+LV)​(b−a),H_{\left\|\cdot\right\|_{C}}(S_{E_{f_{1}}},S_{E_{f_{2}}})\leq\frac{(b-a)\eta}{1-\tfrac{1}{\tau}L_{f}(1+L_{V})(b-a)},

where Lf=max⁡(Lf1,Lf2)L_{f}=\max(L_{f_{1}},L_{f_{2}}) and H∥⋅∥CH_{\left\|\cdot\right\|_{C}} denotes the Pompeiu-Housdorff functional with respect to ∥⋅∥C\left\|\cdot\right\|_{C} on C​[a,b].C[a,b].

Proof.

In the condition of Theorem 11, the operators Ef1E_{f_{1}} and Ef2E_{f_{2}} are cic_{i}-weakly Picard operators, i=1,2i=1,2. Let Xα:={x∈C​[a,b]|x​(a)=α}X_{\alpha}:=\{x\in C[a,b]|\ x(a)=\alpha\}.

It is clear that Ef1|Xα=Bf1,Ef2|Xα=Bf2.E_{f_{1}}|_{X_{\alpha}}=B_{f_{1}},\ E_{f_{2}}|_{X_{\alpha}}=B_{f_{2}}. Therefore,

|Ef12​(x)−Ef1​(x)|≤1τ​Lf1​(1+LV)​(b−a)​|Ef1​(x)−x|,\left|E_{f_{1}}^{2}(x)-E_{f_{1}}(x)\right|\leq\tfrac{1}{\tau}L_{f_{1}}(1+L_{V})(b-a)\left|E_{f_{1}}(x)-x\right|,
|Ef22​(x)−Ef2​(x)|≤1τ​Lf2​(1+LV)​(b−a)​|Ef2​(x)−x|,\left|E_{f_{2}}^{2}(x)-E_{f_{2}}(x)\right|\leq\tfrac{1}{\tau}L_{f_{2}}(1+L_{V})(b-a)\left|E_{f_{2}}(x)-x\right|,

for all x∈C​[a,b].x\in C[a,b]. Now, choosing α1=1τ​Lf1​(1+LV)​(b−a)​and ​α2=1τ​Lf2​(1+LV)​(b−a)\alpha_{1}=\tfrac{1}{\tau}L_{f_{1}}(1+L_{V})(b-a)\ \text{and }\alpha_{2}=\tfrac{1}{\tau}L_{f_{2}}(1+L_{V})(b-a), we get that Ef1E_{f_{1}} and Ef2E_{f_{2}} are cic_{i}-weakly Picard operators, i=1,2i=1,2 with c1=(1−α1)−1c_{1}=(1-\alpha_{1})^{-1}\ and c2=(1−α2)−1\ c_{2}=(1-\alpha_{2})^{-1}. From (5) we obtain that

‖Ef1​(x)−Ef2​(x)‖C≤(b−a)​η,\left\|E_{f_{1}}(x)-E_{f_{2}}(x)\right\|_{C}\leq(b-a)\eta,

∀x∈C​[a,b].\forall x\in C[a,b]. Applying Theorem 16 we have that

H∥⋅∥C​(SEf1,SEf2)≤(b−a)​η1−1τ​Lf​(1+LV)​(b−a),H_{\left\|\cdot\right\|_{C}}(S_{E_{f_{1}}},S_{E_{f_{2}}})\leq\frac{(b-a)\eta}{1-\tfrac{1}{\tau}L_{f}(1+L_{V})(b-a)},

where Lf=max⁡(Lf1,Lf2)L_{f}=\max(L_{f_{1}},L_{f_{2}}) and H∥⋅∥CH_{\left\|\cdot\right\|_{C}} is the Pompeiu-Housdorff functional with respect to ∥⋅∥C\left\|\cdot\right\|_{C} on C​[a,b].C[a,b]. ∎

8. Applications

Let us now discuss some applications of the general result. Consider the first order integro-differential equation of Volterra type (see [3], [4], [6])

(6) x′(t)=f(t,x(t),∫atk(t,s,x(s)ds),t∈[a,b],x^{\prime}(t)=f(t,x(t),\int\nolimits_{a}^{t}k(t,s,x(s)ds),t\in[a,b],

with the initial condition

(7) x​(0)=α.x(0)=\alpha.

For this equations the conditions (C1)-(C3) becomes

  • (C1)

    α∈ℝ\alpha\in\mathbb{R}, f∈C​([a,b]×ℝ2,ℝ),k∈C​([a,b]×[a,b]×ℝ,ℝ)f\in C([a,b]\times\mathbb{R}^{2},\mathbb{R}),\ k\in C([a,b]\times[a,b]\times\mathbb{R},\mathbb{R}) are given;

  • (C2)

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

    |f​(t,u1,u2)−f​(t,v1,v2)|≤Lf​∑i=12|ui−vi|,t∈[a,b],ui,vi∈ℝ,i=1,2.\left|f(t,u_{1},u_{2})-f(t,v_{1},v_{2})\right|\leq L_{f}\sum_{i=1}^{2}\left|u_{i}-v_{i}\right|,t\in[a,b],u_{i},v_{i}\in\mathbb{R},i=1,2.
  • (C3)

    there exists Lk>0L_{k}>0 such that

    |k​(t,s,u)−k​(t,s,v)|≤Lk​|u−v|,∀t,s∈[a,b],u,v∈ℝ.\left|k(t,s,u)-k(t,s,v)\right|\leq L_{k}\left|u-v\right|,\forall t,s\in[a,b],\ u,v\in\mathbb{R}.

From this conditions and the above results we have

Theorem 18.

We suppose that the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}) are satisfied. Then the problem (6)–(7) has in C​[a,b]C[a,b] a unique solution and this solution is the uniform limit of the successive approximations.

Theorem 19.

We suppose that:

  • (a)

    the conditions (C1),(C2)(C_{1}),\ (C_{2}) and (C3)(C_{3}) are satisfied;

  • (b)

    f​(t,⋅,⋅):ℝ2→ℝ2f(t,\cdot,\cdot):\mathbb{R}^{2}\rightarrow\mathbb{R}^{2} is increasing;

  • (c)

    k:C​([a,b]×[a,b]×ℝ),ℝ→ℝk:C([a,b]\times[a,b]\times\mathbb{R),\mathbb{R}}\rightarrow\mathbb{R} is increasing.

Let xx be a solution of equation (1) and yy a solution of the inequality

y′(t)≤f(t,y(t),∫atk(t,s,y(s)ds),t∈[a,b].y^{\prime}(t)\leq f(t,y(t),\int\nolimits_{a}^{t}k(t,s,y(s)ds),\ t\in[a,b].

Then y​(a)≤x​(a)​ implies that ​y≤xy(a)\leq x(a)\text{ implies that }y\leq x.

Theorem 20.

We suppose that fi∈C​([a,b]×ℝ2,ℝ),i=1,2,f_{i}\in C([a,b]\times\mathbb{R}^{2},\mathbb{R}),i=1,2, satisfy the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}). Furthermore, we suppose that:

  • (i)

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

  • (ii)

    f2​(t,⋅,⋅):ℝ2→ℝ2f_{2}(t,\cdot,\cdot):\mathbb{R}^{2}\rightarrow\mathbb{R}^{2} is increasing;

  • (iii)

    k:C​([a,b]×[a,b]×ℝ,ℝ)→ℝk:C([a,b]\times[a,b]\times\mathbb{R,\mathbb{R})}\rightarrow\mathbb{R} is increasing.

Let xi∈C1​[a,b]x_{i}\in C^{1}[a,b] be a solution of the equation

xi′(t)=fi(t,x(t),∫atk(t,s,y(s)ds),t∈[a,b] and i=1,2,3.x_{i}^{\prime}(t)=f_{i}(t,x(t),\int\nolimits_{a}^{t}k(t,s,y(s)ds),\ t\in[a,b]\text{ and }i=1,2,3.

If, x1​(a)≤x2​(a)≤x3​(a)x_{1}(a)\leq x_{2}(a)\leq x_{3}(a), then x1≤x2≤x3.x_{1}\leq x_{2}\leq x_{3}.

Theorem 21.

We suppose that αi,fi,i=1,2\alpha_{i},f_{i},i=1,2 satisfy the conditions (C1),(C2)(C_{1}),(C_{2}) and (C3)(C_{3}). Furthermore, we suppose that there exists ηi>0,i=1,2\eta_{i}>0,i=1,2 such that

  1. (i)

    |α1​(t)−α2​(t)|≤η1,∀t∈[a,b];\left|\alpha_{1}(t)-\alpha_{2}(t)\right|\leq\eta_{1},\forall t\in[a,b];

  2. (ii)

    |f1​(t,u1,u2)−f2​(t,u1,u2)|≤η2,∀t∈[a,b],ui∈ℝ,i=1,2.\left|f_{1}(t,u_{1},u_{2})-f_{2}(t,u_{1},u_{2})\right|\leq\eta_{2},\forall t\in[a,b],u_{i}\in\mathbb{R},i=1,2.

Then

‖x1∗​(t;α1,f1)−x2∗​(t;α2,f2)‖≤η1+(b−a)​η21−1τ​Lf​(1+Lk)​(b−a),\left\|x_{1}^{\ast}(t;\alpha_{1},f_{1})-x_{2}^{\ast}(t;\alpha_{2},f_{2})\right\|\leq\frac{\eta_{1}+(b-a)\eta_{2}}{1-\tfrac{1}{\tau}L_{f}(1+L_{k})(b-a)},

where xi∗​(t;αi,fi),i=1,2x_{i}^{\ast}(t;\alpha_{i},f_{i}),i=1,2 are the solution of the problem (6)–(7) with respect to αi,fi\alpha_{i},f_{i} and Lf=max⁡(Lf1,Lf2).L_{f}=\max(L_{f_{1}},L_{f_{2}}).

Acknowledgement 22.

This work has been supported by grant 2​-CEx06​-11​-96​/19.09.2006.

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