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Boundary Value Problems for Delay Differential Systems
Advances in Difference Equations volume 2010, Article number: 593834 (2010)
Abstract
Conditions are derived of the existence of solutions of linear Fredholm's boundaryvalue problems for systems of ordinary differential equations with constant coefficients and a single delay, assuming that these solutions satisfy the initial and boundary conditions. Utilizing a delayed matrix exponential and a method of pseudoinverse by MoorePenrose matrices led to an explicit and analytical form of a criterion for the existence of solutions in a relevant space and, moreover, to the construction of a family of linearly independent solutions of such problems in a general case with the number of boundary conditions (defined by a linear vector functional) not coinciding with the number of unknowns of a differential system with a single delay. As an example of application of the results derived, the problem of bifurcation of solutions of boundaryvalue problems for systems of ordinary differential equations with a small parameter and with a finite number of measurable delays of argument is considered.
1. Introduction
First we mention auxiliary results regarding the theory of differential equations with delay. Consider a system of linear differential equations with concentrated delay
assuming that
where is an real matrix, and is an dimensional real column vector, with components in the space (where ) of functions integrable on with the degree ; the delay is a function measurable on ; is a given vector function with components in . Using the denotations
where is an dimensional zero column vector, and assuming , it is possible to rewrite (1.1), (1.2) as
where is an dimensional column vector defined by the formula
We will investigate (1.5) assuming that the operator maps a Banach space of absolutely continuous functions into a Banach space of function integrable on with the degree ; the operator maps the space into the space . Transformations of (1.3), (1.4) make it possible to add the initial vector function , to nonhomogeneity, thus generating an additive and homogeneous operation not depending on , and without the classical assumption regarding the continuous connection of solution with the initial function at .
A solution of differential system (1.5) is defined as an dimensional column vector function , absolutely continuous on with a derivative in a Banach space of functions integrable on with the degree satisfying (1.5) almost everywhere on . Throughout this paper we understand the notion of a solution of a differential system and the corresponding boundary value problem in the sense of the above definition.
Such treatment makes it possible to apply the welldeveloped methods of linear functional analysis to (1.5) with a linear and bounded operator . It is well known (see, e.g., [1–4]) that a nonhomogeneous operator equation (1.5) with delayed argument is solvable in the space for an arbitrary righthand side and has an dimensional family of solutions in the form
where the kernel is an Cauchy matrix defined in the square which is, for every a solution of the matrix Cauchy problem:
where if , and is the null matrix. A fundamental matrix for the homogeneous (1.5) has the form , .
A serious disadvantage of this approach, when investigating the aboveformulated problem, is the necessity to find the Cauchy matrix [5, 6]. It exists but, as a rule, can only be found numerically. Therefore, it is important to find systems of differential equations with delay such that this problem can be solved directly. Below, we consider the case of a system with what is called a single delay [7]. In this case, the problem of how to construct the Cauchy matrix is solved analytically thanks to a delayed matrix exponential, as defined below.
2. A Delayed Matrix Exponential
Consider a Cauchy problem for a linear nonhomogeneous differential system with constant coefficients and with a single delay
with constant matrix , , , and an unknown vector solution . Together with a nonhomogeneous problem (2.1), (2.2), we consider a related homogeneous problem
Denote by a matrix function called a delayed matrix exponential (see [7]) and defined as
This definition can be reduced to the following expression:
where is the greatest integer function. The delayed matrix exponential equals a unit matrix on and represents a fundamental matrix of a homogeneous system with a single delay.
We mention some of the properties of given in [7]. Regarding the system without delay , the delayed matrix exponential does not have the form of a matrix series, but it is a matrix polynomial, depending on the time interval in which it is considered. It is easy to prove directly that the delayed matrix exponential satisfies the relations
By integrating the delayed matrix exponential, we get
where . If, moreover, the matrix is regular, then
Delayed matrix exponential , is an infinitely many times continuously differentiable function except for the nodes , where there is a discontinuity of the derivative of order :
The following results (proved in [7] and being a consequence of (1.7) with as well) hold.
Theorem 2.1.

(A)
The solution of a homogeneous system (2.3) with a single delay satisfying the initial condition (2.4) where is an arbitrary continuously differentiable vector function can be represented in the form
(2.11)

(B)
A particular solution of a nonhomogeneous system (2.1) with a single delay satisfying the zero initial condition if can be represented in the form
(2.12)

(C)
A solution of a Cauchy problem of a nonhomogeneous system with a single delay (2.1) satisfying a constant initial condition
(2.13)
has the form
3. Main Results
Without loss of generality, let . The problem (2.1), (2.2) can be transformed to an equation of type (1.1) (see (1.5)):
where, in accordance with (1.3), (1.4),
A general solution of a Cauchy problem for a nonhomogeneous system (3.1) with a single delay satisfying a constant initial condition
has the form (1.7):
where, as can easily be verified (in view of the abovedefined delayed matrix exponential) by substituting into (3.1),
is a normal fundamental matrix of the homogeneous system related to (3.1) (or (2.1)) with the initial data , and the Cauchy matrix has the form
Obviously,
and, therefore, the initial problem (3.1) for systems of ordinary differential equations with constant coefficients and a single delay, satisfying a constant initial condition, has an parametric family of linearly independent solutions
Now we will consider a general Fredholm boundary value problem for system (3.1).
3.1. Fredholm Boundary Value Problem
Using the results in [8, 9], it is easy to derive statements for a general boundary value problem if the number of boundary conditions does not coincide with the number of unknowns in a differential system with a single delay.
We consider a boundary value problem
assuming that
or, using (3.2), in an equivalent form
where is an dimensional constant vector column, and is a linear vector functional. It is well known that, for functional differential equations, such problems are of Fredholm's type (see, e.g., [1, 9]). We will derive the necessary and sufficient conditions and a representation (in an explicit analytical form) of the solutions of the boundary value problem (3.11), (3.12).
We recall that, because of properties (3.6)–(3.7), a general solution of system (3.11) has the form
In the algebraic system
derived by substituting (3.13) into boundary condition (3.12); the constant matrix
has a size of . Denote
where, obviously, . Adopting the wellknown notation (e.g., [9]), we define an dimensional matrix
which is an orthogonal projection projecting space to of the matrix where is an identity matrix and an dimensional matrix
which is an orthogonal projection projecting space to of the transposed matrix where is an identity matrix and is an dimensional matrix pseudoinverse to the dimensional matrix . Using the property
where , we will denote by a dimensional matrix constructed from linearly independent rows of the matrix . Moreover, taking into account the property
we will denote by an dimensional matrix constructed from linearly independent columns of the matrix .
Then (see [9, page 79, formulas (), ()]) the condition
is necessary and sufficient for algebraic system (3.14) to be solvable where is (throughout the paper) a dimensional column zero vector. If such condition is true, system (3.14) has a solution
Substituting the constant defined by (3.22) into (3.13), we get a formula for a general solution of problem (3.11), (3.12):
where is a generalized Green operator. If the vector functional satisfies the relation [9, page 176]
which is assumed throughout the rest of the paper, then the generalized Green operator takes the form
where
is a generalized Green matrix, corresponding to the boundary value problem (3.11), (3.12), and the Cauchy matrix has the form of (3.6). Therefore, the following theorem holds (see [10]).
Theorem 3.1.
Let be defined by (3.15) and . Then the homogeneous problem
corresponding to the problem (3.11), (3.12) has exactly linearly independent solutions
Nonhomogeneous problem (3.11), (3.12) is solvable if and only if and satisfy linearly independent conditions (3.21). In that case, this problem has an dimensional family of linearly independent solutions represented in an explicit analytical form (3.23).
The case of implies the inequality . If , the boundary value problem is overdetermined, the number of boundary conditions is more than the number of unknowns, and Theorem 3.1 has the following corollary.
Corollary 3.2.
If , then the homogeneous problem (3.27) has only the trivial solution. Nonhomogeneous problem (3.11), (3.12) is solvable if and only if and satisfy linearly independent conditions (3.21) where Then the unique solution can be represented as
The case of is interesting as well. Then the inequality , holds. If the boundary value problem is not fully defined. In this case, Theorem 3.1 has the following corollary.
Corollary 3.3.
If , then the homogeneous problem (3.27) has an dimensional family of linearly independent solutions
Nonhomogeneous problem (3.11), (3.12) is solvable for arbitrary and and has an parametric family of solutions
Finally, combining both particular cases mentioned in Corollaries 3.2 and 3.3, we get a noncritical case.
Corollary 3.4.
If (i.e., ), then the homogeneous problem (3.27) has only the trivial solution. The nonhomogeneous problem (3.11), (3.12) is solvable for arbitrary and and has a unique solution
where
is a Green operator, and
is a related Green matrix, corresponding to the problem (3.11), (3.12).
4. Perturbed Boundary Value Problems
As an example of application of Theorem 3.1, we consider the problem of bifurcation from point of solutions , satisfying, for a.e. , systems of ordinary differential equations
where is constant matrix, is an matrix, , consisting of matrices , , having entries in , is a small parameter, delays are measurable on , , , , , , and satisfying the initial and boundary conditions
where , is a given vector function with components in , and is a linear vector functional. Using denotations (1.3), (1.4), and (1.6), it is easy to show that the perturbed nonhomogeneous linear boundary value problem (4.1), (4.2) can be rewritten as
In (4.3) we specify as a single delay defined by formula ;
is an dimensional column vector, and is an dimensional column vector given by
It is easy to see that . The operator maps the space into the space
that is, . Using denotation (1.3) for the operator , we have the following representation:
where
is the characteristic function of the set
Assume that nonhomogeneities and are such that the shortened boundary value problem
being a particular case of (4.3) for , does not have a solution. In such a case, according to Theorem 3.1, the solvability criterion (3.21) does not hold for problem (4.10). Thus, we arrive at the following question.
Is it possible to make the problem ( 4.10 ) solvable by means of linear perturbations and, if this is possible, then of what kind should the perturbations and the delays , be for the boundary value problem ( 4.3 ) to be solvable?
We can answer this question with the help of the matrix
where
constructed by using the coefficients of the problem (4.3).
Using the Vishik and Lyusternik method [11] and the theory of generalized inverse operators [9], we can find bifurcation conditions. Below we formulate a statement (proved using [8] and [9, page 177]) which partially answers the above problem. Unlike an earlier result [9], this one is derived in an explicit analytical form. We remind that the notion of a solution of a boundary value problem was specified in part 1.
Theorem 4.1.
Consider system
where is constant matrix, is an matrix, , consisting of matrices , , having entries in , is a small parameter, delays are measurable on , , , , , with the initial and boundary conditions
where , is a given vector function with components in , and is a linear vector functional, and assume that
(satisfying ) and are such that the shortened problem
does not have a solution. If
then the boundary value problem (4.13), (4.14) has a set of linearly independent solutions in the form of the series
converging for fixed , where is an appropriate constant characterizing the domain of the convergence of the series (4.18), and are suitable coefficients.
Remark 4.2.
Coefficients , , in (4.18) can be determined. The procedure describing the method of their deriving is a crucial part of the proof of Theorem 4.1 where we give their form as well.
Proof.
Substitute (4.18) into (4.3) and equate the terms that are multiplied by the same powers of . For , we obtain the homogeneous boundary value problem
which determines .
By Theorem 3.1, the homogeneous boundary value problem (4.19) has an parametric family of solutions where the dimensional column vector can be determined from the solvability condition of the problem for .
For , we get the boundary value problem
which determines .
It follows from Theorem 3.1 that the solvability criterion (3.21) for problem (4.20) has the form
from which we receive, with respect to , an algebraic system
The righthand side of (4.22) is nonzero only in the case that the shortened problem does not have a solution. The system (4.22) is solvable for arbitrary and if the condition (4.17) is satisfied [9, page 79]. In this case, system (4.22) becomes resolvable with respect to up to an arbitrary constant vector from the nullspace of matrix and
This solution can be rewritten in the form
where
and is an dimensional matrix whose columns are a complete set of linearly independent columns of the dimensional matrix with
So, for the solutions of the problem (3.14), we have the following formulas:
Assuming that (3.24) and (4.17) hold, the boundary value problem (4.20) has the parametric family of solutions
Here, is an dimensional constant vector, which is determined at the next step from the solvability condition of the boundary value problem for
For , we get the boundary value problem
which determines . The solvability criterion for the problem (4.29) has the form (in computations below we need a composition of operators and the order of operations is following the inner operator which acts to matrices and vector function having an argument denoted by and the outer operator which acts to matrices having an argument denoted by
or, equivalently, the form
Assuming that (4.17) holds, the algebraic system (4.31) has the following family of solutions:
where
So, for the parametric family of solutions of the problem (4.20), we have the following formula:
where
Again, assuming that (4.17) holds, the boundary value problem (4.29) has the parametric family of solutions
Here, is an dimensional constant vector, which is determined at the next step from the solvability condition of the boundary value problem for :
The solvability criterion for the problem (4.37) has the form
or, equivalently, the form
Under condition (4.17), the last equation has the parametric family of solutions
where
So, for the coefficient , we have the following formula:
where
Continuing this process, by assuming that (4.17) holds, it follows by induction that the coefficients of the series (4.18) can be determined, from the relevant boundary value problems as follows:
where
and .
The convergence of the series (4.18) can be proved by traditional methods of majorization [9, 11].
In the case , the condition (4.17) is equivalent with , and problem (4.13), (4.14) has a unique solution.
Example 4.3.
Consider the linear boundary value problem for the delay differential equation
where, as in the above, and are measurable functions. Using the symbols and (see (1.3), (1.4), (1.6), and (4.7)), we arrive at the following operator system:
where is an matrix , and
Under the condition that the generating boundary value problem has no solution, we consider the simplest case of . Using the delayed matrix exponential (2.5), it is easy to see that, in this case, is a normal fundamental matrix for the homogeneous unperturbed system , and
Then the matrix has the form
If , problem (4.46) has a unique solution with the properties
Let, say, where , , then
or, equivalently,
Now the matrix turns into
and the boundary value problem (4.46) is uniquely solvable if
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Acknowledgments
The authors highly appreciate the work of the anonymous referee whose comments and suggestions helped them greatly to improve the quality of the paper in many aspects. The first author was supported by Grant 1/0771/08 of the Grant Agency of Slovak Republic (VEGA) and Project APVV070007 of Slovak Research and Development Agency. The second author was supported by Grant 201/08/0469 of Czech Grant Agency and by the Council of Czech Government MSM 0021630503, MSM 0021630519, and MSM 0021630529. The third author was supported by Project M/342008 of Ukrainian Ministry of Education. The fourth author was supported by Grant 1/0090/09 of the Grant Agency of Slovak Republic (VEGA) and project APVV070007 of Slovak Research and Development Agency.
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Boichuk, A., Diblík, J., Khusainov, D. et al. Boundary Value Problems for Delay Differential Systems. Adv Differ Equ 2010, 593834 (2010). https://doi.org/10.1155/2010/593834
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DOI: https://doi.org/10.1155/2010/593834
Keywords
 Parametric Family
 Homogeneous Problem
 Dimensional Matrix
 Dimensional Family
 Cauchy Matrix