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Linear overdetermined boundary value problems in Hilbert space
Boundary Value Problems volume 2014, Article number: 140 (2014)
The general linear boundary value problem for an abstract functional differential equation is considered in the case that the number of boundary conditions is greater than the dimension of the null-space to the corresponding homogeneous equation. Sufficient conditions of the solvability of the problem are obtained. A case of a functional differential system with aftereffect is considered separately.
Linear boundary value problems (BVPs) for differential equations with ordinary derivatives that lack the everywhere and unique solvability are met with in various applications. Among these applications are some problems in oscillation theory (see, for examples, []) and economic dynamics []. Results on the solvability and solutions representation for these BVPs are widely used as an instrument of investigating weakly nonlinear BVPs []. General results concerning linear BVPs for an abstract functional differential equation (AFDE) are given in []. In this paper, we consider a case that the number of linearly independent boundary conditions is greater than the dimension of the null-space of the corresponding homogeneous equation and obtain sufficient conditions of the solvability without recourse to the adjoint BVP and an extension of the original BVP. Our approach is based in essence on the assumption that the derivative of the solution does belong to a Hilbert space. Then we consider a system of functional differential equations that, formally speaking, is a concrete realization of the AFDE and, on the other hand, covers many kinds of dynamic models with aftereffect (integro-differential, delayed differential, differential difference) [–]. For this case sufficient conditions are derived in an explicit form.
where is a linear bounded operator, D and B are Banach spaces such that D is isomorphic to the direct product . Let us denote by an isomorphism and let .
A linear operator acting from the direct product of the Banach spaces B and into a Banach space D is defined by a pair of linear operators and in such a way that
A linear operator acting from a space D into a direct product is defined by a pair of linear operators and so that
Under the norm
the space is Banach (here and in what follows, denotes a norm in ). If the bounded operator is the inverse to the bounded operator , then
, , .
where I is the identity operator. We will identify the finite-dimensional operator with a vector , , such that , .
Denote the components of the vector functional r by . If is a linear vector functional, and is a vector with components , then lX denotes the -matrix, whose columns are the values of the vector functional l on the components of , ; .
Applying ℒ to both parts of (2.4), we obtain the decomposition
where is the principal part, and is the finite-dimensional part of ℒ. Similarly, by application of ℓ to the two parts of (2.4), we get
where is a linear bounded vector functional.
Let be a linear bounded vector functional with linearly independent components, . The system
is called a linear boundary value problem.
is the adjoint one to the operator
Taking into account the isomorphism between the spaces and , we therefore call the equation
the adjoint equation to the problem (2.8).
In the sequel it is assumed that the so-called principal BVP
is uniquely solvable for any , . Recall that in such a case we have the representation [] (Theorem 1.16, p.11)
to the solution of (2.10) with X called the fundamental vector and G called the Green operator.
Problem (2.7) covers a wide class of BVPs for ordinary differential systems, differential delay systems, some singular and impulsive systems []. This problem is well-posed if . In such a situation, BVP (2.7) is uniquely solvable for any and if and only if the matrix
where is the j th element of X, is nonsingular, i.e..
In the case that BVP (2.7) lacks the everywhere and unique solvability, namely, it is solvable if and only if the right-hand side is orthogonal to all the solutions of the homogeneous adjoint equation (2.9), i.e. [] (Corollary 1.15, p.11).
In what follows we derive conditions of solvability for (2.7) in a more explicit form without recourse to the adjoint BVP. Our approach is based in essence on the assumption that the space B is a Hilbert space H with an inner product .
A case of AFDE
Consider BVP (2.7) under the assumption that and the system , can be split into two subsystems and such that the BVP
is uniquely solvable. Without loss of generality we will consider that is formed by the first n components of ℓ and the elements of in (3.1) are the corresponding components of γ. Thus will stand for the final components of ℓ, and elements of are defined as the final components of γ. For , , we put . Thus in the cases that a vector V is expressed by a complicated formula we will use instead of to indicate the j th component of V.
Define the vector functional , by the equality
and preserve the symbol for an element of H that generates the functional : for any
Let us define the -matrix by the equalities
Let W be nonsingular. Then BVP (2.7) is solvable for anyof the form
andis arbitrary element that is orthogonal to each, .
The general solution of the equation has the representation
with an arbitrary . Apply to both parts of (3.2):
By the unique solvability of BVP (3.1) the condition holds, therefore the equation
is uniquely solvable with respect to α:
Hence, for any ,
Rewrite this as the equation with respect to :
The left-hand side of (3.5) defines a linear bounded vector functional λ over the space H:
, with components that are linear bounded functionals. Therefore,
Thus, for any , the representation
Put . Then (3.8) takes the form
To complete the proof, it remains now to substitute c into (3.7). □
A case of systems with aftereffect
In this section, we consider a system of functional differential equations with aftereffect that, formally speaking, is a concrete realization of the AFDE, and, on the other hand, it covers many kinds of dynamic models with aftereffect (integro-differential, delayed differential, differential difference) [, , ].
Despite the case considered in Sections 2, 3 is more general, we derive here conditions of the solvability in detail since the corresponding transformations are based on the properties of operators and spaces as applied to the case under consideration.
Let us introduce the functional spaces where operators and equations are considered. Fix a segment . By we denote the Hilbert space of square summable functions endowed with the inner product (⋅′ is the symbol of transposition). The space is the space of absolutely continuous functions such that with the norm , where stands for the norm of . Thus we have here , , , and , , , , (see (2.2)-(2.4)).
Consider the functional differential equation
where the linear bounded operator is defined by
the elements of the kernel are measurable on the set and such that , , , -matrix A has elements that are square summable on . Therefore, we have here , (see (2.5)).
Recall that, under some natural assumptions, the following equations can be rewritten in the form (4.1):
• the differential equation with concentrated delay
(here, for any measurable function such that , , stands for a given function if );
• the differential equation with distributed delay
(with the Stieltjes integral);
• the integro-differential equation
where is the identity -matrix, each column of the -matrix is a unique solution to the Cauchy problem
where is the i th column of A.
The solution of (4.1) with the initial condition has the representation
where is the Cauchy matrix of the operator ℒ. This matrix can be defined (and constructed) as the solution to
under the condition .
The matrix is expressed in terms of the resolvent kernel of the kernel . Namely,
Thus , and the above equation for is the well-known relationship between the kernel and its resolvent kernel .
The general solution of (4.1) has the form
with an arbitrary .
The general linear BVP is the system (4.1) supplemented by linear boundary conditions
where is a linear bounded vector functional. Let us recall the representation of ℓ:
Here Ψ is a constant -matrix, Φ is -matrix with elements that are square summable on . We assume that the components , of ℓ are linearly independent.
where is the j th column of X, is nonsingular, i.e.. It should be noted that this condition cannot be verified immediately because X cannot be (as a rule) evaluated explicitly. In addition, even if X were known, then the elements of ℓX, generally speaking, could not be evaluated explicitly. By the theorem about inverse operators, the matrix ℓX is invertible if one can find an invertible matrix Γ such that . As has been shown in [], such a matrix Γ for the invertible matrix ℓX always can be found among the matrices , where is a vector functional near ℓ, and is an approximation of X. That is why the basis of the so-called constructive study of linear BVPs includes a special technique of approximate constructing the solutions to FDE with guaranteed explicit error bounds as well as the reliable computing experiment (RCE) [, , ] which opens a way to the computer-assisted study of BVPs.
We assume in the sequel that and the system , can be split into two subsystems and such that the BVP
is uniquely solvable. Without loss of generality we will consider that is formed by the first n components of ℓ and the elements of in (4.6) are the corresponding components of γ. Thus will stand for the final components of ℓ, and elements of are defined as the final components of γ. Let us write in the form
where and are the corresponding rows of and Ψ, respectively. Similarly,
andis an arbitrary function that is orthogonal to each column of:
Let us apply to both parts of (4.3):
In virtue of the unique solvability of BVP (4.6), the condition holds, therefore the equation
is uniquely solvable with respect to α:
Hence, for any ,
Now we show that the left-hand side of the latter equality can be written, for all , in the form
with a -matrix F whose columns belong to .
An explicit form of F is simple to derive by elementary transformations taking into account (4.5) and the properties of the Cauchy matrix. To do this, first note that
This follows from (4.2) and the equality . Next, we have
Notice that the interchangeability of the order of integration in the iterated integrals above is proved in []. In a similar way,
Now it remains to find such that
As is well known, any can be represented in the form
with and such that . By virtue of the condition , we obtain after substitution of (4.14) into (4.13) that the vector gives the corresponding f (see (4.14)) that solves (4.13). This completes the proof. □
In view of Theorem 2, the solvability of BVP (4.1), (4.4) can be investigated on the base of the reliable computing experiment [, , ]. A somewhat different approach to the study of BVP (4.1), (4.4) with is proposed in [].
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The author thanks the referees for their careful reading of the manuscript and useful comments. The author acknowledges the support by the company Prognoz, Perm.
The author declares that he has no competing interests.