We consider an integro-differential equation with two time lags and we prove the existence, uniqueness and convergence of the sequence of the successive approximation by using contraction principle and step method with a weaker Lipschitz condition.
Also, we propose a new algorithm of successive approximation sequence generated by the step method and we give an example to illustrate the applications of the abstract results.
Authors
V.Ilea Department of Mathematics, Babes-Bolyai University Cluj-Napoca, Romania
Diana Otrocol
Tiberiu Popoviciu Institutue of Numerical Analysis
M.A. Serban Department of Mathematics, Babes-Bolyai University Cluj-Napoca, Romania
D.Trif Department of Mathematics, Babes-Bolyai University Cluj-Napoca, Romania
Keywords
Integro-differential equation; two time lags, step method; Picard operators; fibre contraction principle.
Paper coordinates
V.Ilea, D. Otrocol, M.A. Serban, D. Trif, Integro-Differential Equation with two time lags, Fixed Point Theory, 13 (2012) no. 1, pp. 85-97.
[1] M. Dobrit¸oiu, I.A. Rus, M.A. S¸erban, An integral equation arising from infectious diseases, via Picard operator, Studia Univ. “Babes-Bolyai”, Mathematica, 52(2007), No. 3, 81-83.
[2] D. Guo, V. Lakshmikantham, X. Liu, Nonlinear Integral Equations in Abstract Spaces, Kluwer Acad. Publ., Dordrecht, 1996.
[3] V.A. Ilea, Functional Differential Equations of First Order with Advanced and Retarded Arguments, Cluj University Press, 2006, (in Romanian).
[4] V.A. Ilea, D. Otrocol, Integro-differential equation with two times modifications, Carpathian J. Math., 27(2011), No. 2, 209-216.
[5] V. Kolmanovskii, A. Mishkis, Applied Theory of Functional Differential Equations, Kluwer Acad. Publ., 1992.
[6] D. Otrocol, Lotka-Volterra Systems with Retarded Argument, Cluj University Press, 2007, (in Romanian).
[7] R. Precup, Positive solution of initial value problem for an integral equation modelling infectious diseases, Seminar of Fixed Point Theory, Cluj-Napoca, 1991, 25-30.
[8] R. Precup, E. Kirr, Analysis of nonlinear integral equation modelling infectious diseases, Proc. Conf. West. Univ. of Timi¸soara, 1997, 178-195.
[9] I.A. Rus, Abstract models of step method which imply the convergence of successive approximations, Fixed Point Theory, 9(2008), No. 1, 293-307.
[10] I.A. Rus, Picard operators and applications, Sci. Math. Jpn., 58(2003), No. 1, 191-219.
[11] I.A. Rus, Picard operators and applications, Seminar on Fixed Point Theory, Cluj-Napoca, 2(2001), 41-58.
[12] I.A. Rus, Some nonlinear functional differential and integral equations, via weakly Picard operator theory: a survey, Carpathian J. Math., 26(2010), No. 2, 230-258.
[13] I.A. Rus, M.A. S¸erban, D. Trif, Step method for some integral equations from biomathematics, Bull. Math. Soc. Sci. Math. Roumanie, 54(102)(2011), No. 2, 167-183.
[14] S. Sakata, T. Hara, Stability regions for linear differential equations with two kinds of time lags, Funkcialaj Ekvacioj, 47(2004), 129-144.
[15] N.L. Trefethen, An extension of Matlab to continuous functions and operators, SIAM J. Sci. Comput., 25(2004), No. 5, 1743-1770.
[16] D. Trif, LibScEig 1.0, > Mathematics > Differential Equations > LibScEig 1.0, http://www.mathworks.com/matlabcentral/fileexchange, 2005.
Paper (preprint) in HTML form
INTEGRO-DIFFERENTIAL EQUATION WITH TWO TIME LAGS
V. ILEA*, D. OTROCOL**, M.-A. ŞERBAN* AND D. TRIF*
* Department of Mathematics, Babeş-Bolyai University
Kogălniceanu Street No. 1, 400084 Cluj-Napoca, Romania
E-mails:{vdarzu,mserban,dtrif}@math.ubbcluj.ro
** Tiberiu Popoviciu Institute of Numerical Analysis of Romanian Academy
Cluj-Napoca, Romania
E-mail: dotrocol@ictp.acad.ro
Abstract
We consider an integro-differential equation with two time lags and we prove the existence, uniqueness and convergence of the sequence of the successive approximation by using contraction principle and step method with a weaker Lipschitz condition. Also, we propose a new algorithm of successive approximation sequence generated by the step method and we give an example to illustrate the applications of the abstract results.
Key Words and Phrases: Integro-differential equation, two time lags, step method, Picard operators, fibre contraction principle.
2010 Mathematics Subject Classification: 47H10, 47N20.
1. Introduction
This paper is concerned with the following integro-differential equation
(1.1)
where and are continuous functions on a Banach space and satisfy certain conditions to be specified later.
Regarding the earlier works on existence, uniqueness and convergence of the sequence of the successive approximation to integro-differential equations with delays and functional-differential equations with delays under different conditions, we refer to Guo et al [2], Kolmanowskii and Mishkis [5], Precup [7], Precup and Kirr [8], I.A. Rus [12] and the references therein. The related results for the existence and uniqueness, convergence of the sequence of the successive approximation, lower and upper solutions to the differential equations with delays can be found in Dobritioiu et al [1], Ilea [3] and Otrocol [6].
The authors Rus, Şerban, Trif [13] have considered the following integral equation
in a Banach space and proved that the sequence of the successive approximation generated by the step method converges to the solution of this integral equation using the results of Rus [9].
Sakata and Hara [14] have considered the linear differential equation with two kinds of time lags
where and are both real and they have studied the dependence on delays towards stability regions.
In the present work we use the ideas of Rus, Şerban, Trif [13] to establish the convergence of the sequence of successive approximation to equation (1.1). Regarding the two delays we have the following cases: and . Here, the authors study the first case, while the second case is studied in [4].
The aim of this paper is to obtain existence and uniqueness theorems using contraction principle and step method. Such kind of results have been proved in [13]. The approach proposed in the present paper is different to the ones in [13] and [1] and it is based on the different time lags. Also, we present here some lower and upper solution result, and a numerical example concerning equation (1.1).
We note that Sakata and Hara study in [14] the stability regions for similar integrodifferential equation with two time lags.
2. Preliminaries
Let and
(2.1)
(2.2)
Relative to (2.1)-(2.2) we consider the following conditions:
is a Banach space, ;
there exists such that
there exists such that
there exists such that
.
We consider the space endowed with the norms and where
The following relation between the Cebyshev and Bielecki norms holds
The problem (2.1)-(2.2) is equivalent with the following fixed point problem:
3. Fibre weakly Picard operator
Let ( ) be a metric space and an operator. In this paper we shall use the terminologies and notations from [13]. For the convenience of the reader we shall recall some of them.
Denote by , the iterate operators of the operator . Also
Definition 3.1. is called a Picard operator (briefly PO) if:
(i) ;
(ii) as , for all .
Definition 3.2. is said to be a weakly Picard operator (briefly WPO) if the sequence converges for all and the limit (which may depend on ) is a fixed point of .
If is a WPO, then we may define the operator by
Obviously . Moreover, if is a PO and we denote by its unique fixed point, then , for each .
Lemma 3.3. Let an ordered metric space and be such that:
(i) the operator are WPOs;
(ii) ;
(iii) the operator is increasing.
Then implies that .
Theorem 3.4. (Fibre contraction principle, Rus [10]) Let ( ) be a metric space and be a complete metric space. Let and be two operators. We suppose that:
(i) is a ;
(ii) is -contraction, for all ;
(iii) if , where , then is continuous in .
Then is a WPO. Moreover, if is PO then is PO.
By induction, from the above result we have:
Theorem 3.5. (Rus [11]) Let ( ), , be some metric spaces. Let
be some operator. We suppose that:
(i) , are complete metric spaces;
(ii) the operator is WPO;
(iii) there exists such that:
are -contractions;
(iv) the operator , are continuous.
Then the operator ,
is . If is PO, then is PO.
4. Existence and uniqueness
In this section we give an existence theorem for the solution of the problem (2.1)(2.2).
Theorem 4.1. In the condition and , the problem (2.1)-(2.2) has in a unique solution and the sequence of successive approximation,
converges uniformly to , for every , with .
Proof. Let and defined by
Note that is a closed subset of , so is a complete metric space.
In a standard way we have
which proves that is Lipschitz with . We can choose sufficiently large such that , so is contraction. Applying the contraction principle we get the conclusion.
Remark 4.2. From the proof of Theorem 4.1, it follows that the operator is PO.
5. Step method
Using step method and contraction principle on each step for the problem (2.1)(2.2), in this section we obtain a better result by replacing the condition ( ) from Theorem 4.1 with ( ).
Let such that . To simplify our presentation we suppose that . In the conditions and the step method for (2.1)-(2.2) consist in the following:
where is the unique solution of ( ), .
So, we have the following result:
Theorem 5.1. In the conditions and we have:
a) the problem (2.1)-(2.2) has in a unique solution ,
b) for each , , the sequence defined by:
Proof. In order to proof this theorem we apply the contraction principle for each step: , where .
For the first step we consider the Banach space , where and the operator defined by
For , we have
We can choose a such that , so is a contraction, therefore .
For the next steps let us consider the following Banach spaces: for given by
and
, with
and the operators defined by
For we have , so is a contraction for a suitable choice of such that . Therefore, we get that .
From condition ( ) we get and from definition of , we have
therefore
is the unique solution in .
Now the question is: Can we put an approximation of instead of , ?
The answer of this question is given by the following theorem:
Theorem 5.2. In the condition of Theorem 5.1, for each , the sequences defined by:
(5.1)
converge and .
Proof. We consider the following Banach spaces (with ):
and the operators:
and
It is easy to see that for fixed the sequence defined by (5.1) means
To prove the conclusion we need to prove that the operator is PO and for this we apply Theorem 3.5.
Since is a constant operator then is -contraction with , so is PO and , where . We have the inequalities:
for all , and
for all . For sufficiently large, , we get that is -contraction and : are -contractions with , so we are in the conditions of Theorem 3.5, therefore is PO and , thus
with and , for all , are defined by (5.1). From condition and from the definitions of , we have
therefore
is the unique solution in .
6. Lower solutions, upper solutions and the solution
In this section we shall prove that the solution of the equation (1.1) is an upper bound of the lower solutions set and a lower bound of the upper solutions set.
Let the integro-differential equation (1.1) under the conditions , and we denote by the unique fixed point of the operator . In addition, we suppose that:
is increasing, for every
is increasing, for every .
We have
Theorem 6.1. We suppose that the conditions are satisfied. The following implications hold:
(a) If then .
(b) If then .
Proof. (a) We consider the operator defined by
Under the conditions the operator is PO and by we have that the operator is increasing. Since all the conditions of the Abstract Gronwall Lemma 3.3 are satisfied, we obtain and the proof is complete.
For (b) the proof is similar.
7. Numerical example
In this section we give a numerical example to illustrate the convergence of the sequence defined in theorem 5.1 to the solution. We consider the following integrodifferential equation:
which has the exact solution .
Numerical method. (For more details see N.L. Trefethen [15], D. Trif [16]) We divide the working interval by the points , (concretely and represents the number of subintervals). On each subinterval , , we find the numerical solution by the form
where are Chebyshev polynomials of degree, , (concretely ), and with , respectively .
Choosing a mesh , on interval [ ] consisting by the knots of Gauss quadrature formula generated by Matlab subprogram [csi,w]=pd(n), the transformation corresponding to each interval construct a local mesh on that subinterval. The coefficients of expansion after the Chebishev polynomials are obtained from values on the local mesh using Fast Fourier Transforms (if is large) or using a matrix generated by the subprogram (n, csi)
(for small)
The same formula allows the quick pass from the local coefficients to the values on local mesh.
The formulae
allow to obtain the coefficients of a primitive for a function given by its coefficients , from multiplication of them with a sparse matrix generated by the subprogram tchebj
Of course, if the primitive is calculated for other interval instead of , the matrix is replaced by , where .
The algorithm from Theorem 5.1 is implemented in the following way in program [X,sol]=step_meth2, which can be obtained from the authors (mserban@math.ubbcluj.ro):
Step 0. We generate a global mesh on by the union of all local meshes on which we also add the points of subintervals. We calculate the values of on the global mesh from the values of the function on the local mesh of the first interval and from the constant value on the other knots.
Step . Taking the values of on the global mesh, we obtain the values of on the local mesh, we calculate the coefficients of on each subinterval, then we get the coefficients of a primitive for on each subinterval and finally we obtain the values of that primitive on the local mesh. We add the contribution of nonintegrated part (where it is used the history from the previous intervals with two steps). The implementation of the formulae from Theorem 5.1 is now immediately, getting the values of the new iteration on the global mesh by a new integration: we pass from the values on the mesh to coefficients, then we use the integration matrix and finally we return to the values in order to find .
Stoping test. We evaluate the difference in norm between the values of and and iterations stop when this is below than a chosen value (concretely ). We represent the graph of solution and the norm of difference for different .
For the efficiency estimation of this algorithm, the integro-differential equation is written in the form of delay differential equation system and we use the Matlab command dde23 to solve it. We impose the relative error to and the absolute error to to obtain a accuracy comparable with the step method. We display the graph of solution.
Results. Running the program we get the following results:
Conclusions. For the chosen example, the step method obtains the solution in 68 iterations with an error of in 0.054 CPU seconds. The Matlab program dde23 needs 0.671 CPU seconds ( 12 times bigger) for a similar precision. The above comparisons validate the step method from the accuracy and efficiency point of view.
Acknowledgment
This work was supported by a grant of the Romanian National Authority for Scientific Research, CNCS - UEFISCDI, project number PN-II-ID-PCE-2011-3-0094.
References
[1] M. Dobriţoiu, I.A. Rus, M.A. Şerban, An integral equation arising from infectious diseases, via Picard operator, Studia Univ. "Babes-Bolyai", Mathematica, 52(2007), No. 3, 81-83.
[2] D. Guo, V. Lakshmikantham, X. Liu, Nonlinear Integral Equations in Abstract Spaces, Kluwer Acad. Publ., Dordrecht, 1996.
[3] V.A. Ilea, Functional Differential Equations of First Order with Advanced and Retarded Arguments, Cluj University Press, 2006, (in Romanian).
[4] V.A. Ilea, D. Otrocol, Integro-differential equation with two times modifications, Carpathian J. Math., 27(2011), No. 2, 209-216.
[5] V. Kolmanovskii, A. Mishkis, Applied Theory of Functional Differential Equations, Kluwer Acad. Publ., 1992.
[6] D. Otrocol, Lotka-Volterra Systems with Retarded Argument, Cluj University Press, 2007, (in Romanian).
[7] R. Precup, Positive solution of initial value problem for an integral equation modelling infectious diseases, Seminar of Fixed Point Theory, Cluj-Napoca, 1991, 25-30.
[8] R. Precup, E. Kirr, Analysis of nonlinear integral equation modelling infectious diseases, Proc. Conf. West. Univ. of Timişoara, 1997, 178-195.
[9] I.A. Rus, Abstract models of step method which imply the convergence of successive approximations, Fixed Point Theory, 9(2008), No. 1, 293-307.
[10] I.A. Rus, Picard operators and applications, Sci. Math. Jpn., 58(2003), No. 1, 191-219.
[11] I.A. Rus, Picard operators and applications, Seminar on Fixed Point Theory, Cluj-Napoca, 2(2001), 41-58.
[12] I.A. Rus, Some nonlinear functional differential and integral equations, via weakly Picard operator theory: a survey, Carpathian J. Math., (2010), No. 2, 230-258.
[13] I.A. Rus, M.A. Şerban, D. Trif, Step method for some integral equations from biomathematics, Bull. Math. Soc. Sci. Math. Roumanie, 54(102)(2011), No. 2, 167-183.
[14] S. Sakata, T. Hara, Stability regions for linear differential equations with two kinds of time lags, Funkcialaj Ekvacioj, 47(2004), 129-144.
[15] N.L. Trefethen, An extension of Matlab to continuous functions and operators, SIAM J. Sci. Comput., 25(2004), No. 5, 1743-1770.
[16] D. Trif, LibScEig 1.0, > Mathematics > Differential Equations > LibScEig 1.0, http://www.mathworks.com/matlabcentral/fileexchange, 2005.