1. Introduction
The foundations of control theory date back to old times [
1,
2,
3,
4], and it has various applications in many fields, such as population dynamics, epidemiology, resource and energy economy, environmental management, optics, communication theory, medical imaging, and astronomy [
5,
6,
7,
8,
9]. In recent years, the necessity of using natural resources, material and technical tools, time, energy, etc., more efficiently has led to an increased relevance of optimal control problems (OCPs).
As we know, an OCP is described by three essential items. The first is the state equation, which describes the behavior of the controlled system. The second is the set of admissible controls, which contains specified functions that take their values in the defined set. The third is a functional of the controls and state variables, which is called the objective function and is determined in accordance with the purpose of the controlled system. When an OCP is examined, first, the existence and uniqueness of the solution of the problem is investigated, then, the necessary and sufficient conditions for the solution are examined, which allows us to provide a method to characterize and find the solutions of the OCPs.
In the present paper, we consider the state equation
with the initial and boundary conditions
where
,
is a convex bounded domain with a smooth boundary
are given numbers,
is the lateral surface of
,
is the Laplacian,
is the gradient, and
is the outward unit normal to
Also,
is a real-valued function satisfying
Further,
where the functions
for
are real-valued measurable functions such that
where
h are complex-valued functions satisfying the conditions
It is obvious that Equation (
1), unlike the standard Schrödinger equation, contains the gradient term
, and this equation is called a linear Schrödinger equation with a specific gradient term (LSEwSGT) [
4].
The objective functional and the set of admissible controls are considered as
respectively, where
is the Tikhonov regularization parameter [
10].
is the space of all Lebesgue functions, the squares of which the moduli are integrable over
is the space of all functions
having the generalized derivatives
in
for all nonnegative integers
equipped with the norm
Similarly, we denote by
the spaces of all the functions
having first-order generalized partial derivative with respect to variable
t in
with the norm
The detailed descriptions of these spaces can be found in [
11,
12].
Thus, we express the OCP investigated in this paper as the problem of finding the minimum of functional (
6) on the set
under conditions (
1) and (
2).
As seen, problems (
1) and (
2) are a Neumann problem, and its solution is defined in the following sense:
Definition 1. A solution u of problems (1) and (2) for each is defined to be an element of satisfying Equation (1) and and Equation (2) and , where for is a Banach space of all functions , for which all the derivatives up to order k are continuous in with the norm . Based on the results in [
13,
14,
15], we give the following theorem for problems (
1) and (
2):
Theorem 1. If the functions h satisfy conditions (3)–(5), then problems (1) and (2) have a unique solution u in Moreover, for u satisfies the estimatefor where the constant does not depend on Also, based on the results in [
15], we write the following theorems for the existence of an optimal solution:
Theorem 2. If the conditions of Theorem 1 are satisfied, then there exists a unique solution of the OCP on a dense subset for and .
Theorem 3. If the conditions of Theorem 1 are satisfied, then for W and the OCP has at least one solution.
There is a large amount of research on OCPs for Schrödinger equations without any specific gradient terms: for instance, in [
16], the authors demonstrate the existence of an optimal control for the cubic nonlinear Schrödinger equation (NLSE) and give the optimality conditions. In [
17], the authors study an OCP with a final functional for a standard linear Schrödinger equation (LSE), give an existence theorem for OCP, and also derive the necessary optimality conditions. In [
18], the author gives the results about the internal controllability of the LSE and NLSE.
In [
19], the necessary and sufficient conditions for the solution of a bilinear OCP for the LSE are obtained. In [
20], the optimality conditions for an LSE with a singular potential are given. In [
4,
21,
22], the authors study OCPs for LSEs. In [
22,
23,
24], the authors prove the existence of solutions of OCPs for systems governed by NLSEs and give the necessary optimality conditions.
As can be seen, all of the aforementioned works are concerned with OCPs for standard Schrödinger equations (linear or nonlinear), that is, the Schrödinger equation does not contain any specific gradient term. But in [
13], the authors prove the existence of the optimal solution for an OCP with a Lions-type functional for the LSEwSGT. In [
25,
26], the existence of the optimal solution and necessary optimality conditions are given for OCPs with a final functional for the NLSEwSGT. Salmanov [
27] gives the existence and uniqueness theorems for a solution of an OCP with a Lions-type functional for the NLSEwSGT.
It should be noted here that the OCPs with a boundary functional for the LSEwSGT have been hardly analyzed. In [
15,
28], the authors demonstrate the existence of optimal solutions for OCPs with a boundary functional for the LSEwSGT.
In the present work, we search the necessary optimality conditions for the OCP with a boundary functional (
6) on the admissible controls set for state Equation (
1). For this purpose, first, we constitute an adjoint problem. Then, we prove the existence and uniqueness of the solution of the adjoint problem. Later, by showing the differentiability of functional (
6) in the sense of Frechet, we obtain a formula for its gradient. Finally, we give a necessary optimality condition in the variational form.
2. Adjoint Problem
In the current section, we constitute an adjoint problem to investigate the differentiability of functional (
6). By using a Lagrange multiplier function, we obtain the adjoint problem as follows:
where
is a solution of problems (
1) and (
2) for any
Definition 2. A solution Φ for problems (8)–(10) is defined to be an element of satisfying the integral identity such that For convenience, let us denote
Thus, we rewrite problems (
8)–(
10) as
As seen above, problems (
12)–(
14) are a boundary value problem with a nonhomogeneous boundary condition. Firstly, we turn problems (
12)–(
14) into a problem with a homogeneous boundary condition. By using the method in [
22], we write problems (
12)–(
14) as
where
, and
z is a solution of the problem
Also,
, and the functions
are the solutions of problems (
18)–(
20) corresponding to the boundary conditions
and
respectively.
In addition to the conditions (
3)–(
5), let
where
is a Banach space, and the norm in
is defined by
Thus, since
, according to the embedding theorem in [
29],
for the solution
u of problems (
1) and (
2). Hence, since
Also, by changing the variable
, we rewrite problems (
18)–(
20) as
where
Based on the results in [
11,
22,
29], with the assumed conditions, we can easily say that problems (
21)–(
23) have a unique solution
in
, and
where the constant
is independent of
Since problems (
21)–(
23) are equivalent to problems (
18)–(
20), it is clear that problems (
18)–(
20) have a unique solution
z in
, and
Under the assumed conditions, from the definition of
F in problems (
15)–(
17) and estimate (
25), it seems that
Definition 3. A solution w of problems (15)–(17) is defined to be an element of satisfying the integral identity such that As in problems (
18)–(
20), by changing the variable
, we transform problems (
15)–(
17) to the problem
where
If we denote the complex conjugate of
by
, we can easily say that
is a solution of problem
where
G is the complex conjugate of
. For convenience, if we denote the variable
by
t and
by
, we rewrite problems (
30)–(
32) as
As seen, analyzing the solution of problems (
15)–(
17) in
is equivalent to analyzing the solution of problems (
33)–(
35) in
. Because problems (
15)–(
17) are a boundary value problem with final time, and also, by applying the variable transformation
to problems (
15)–(
17), we obtain an initial boundary value problem, i.e., problems (
15)–(
17) and (
33)–(
35) are symmetric.
Definition 4. A function in satisfying the integral identity such that will be called a solution of problems (33)–(35) in . Now, to prove the existence and uniqueness of the solution of problems (
33)–(
35), we consider the auxiliary problem
where
Also, let the functions
and, additionally, (
4),
satisfy the condition
for
Definition 5. A solution u of problems (37)–(39) is defined to be an element of satisfying Equation (37) , (38) and (39) . For the solution of problems (
37)–(
39), we can easily prove the following theorem by Galerkin’s method:
Theorem 4. Let the functions r and satisfy conditions (3), (4), and (40), and let . Then, problems (37)–(39) have a unique solution u in in the meaning of Definition 5. Moreover, there is a constant , which does not depend on h, such that Theorem 5. Let the functions r and for satisfy conditions (3), (4), and (40), and let . Then, problems (33)–(35) have a unique solution ϕ in in the meaning of Definition 4, and ϕ satisfies the estimatewhere the constant is independent from G. Proof. We use the method in [
30], p. 115, Theorem 2.3, for the proof of Theorem 5. We approximate the function
by the functions
such that
Thus, for
, we obtain the problem
Since
for each
, we deduce from Theorem 4 that problems (
44)–(
46) have a unique solution
in
corresponding to
for each
.
It is obvious that the functions
for each
satisfy the integral identity
for any
and
, and the conditions
If we denote
for each
, it is written that
. Thus, the functions
for each
satisfy (
47)–(
49), that is,
If we substitute
for the test function
in (
50), we get
Using the formula of integration by parts and conditions (
4) and (
51) in (
53), we have
If we subtract its complex conjugate from the equality above, we get
In (
54), if we use the equalities
and the conditions
and (
51), we obtain
which implies that
by the Cauchy–Schwarz inequality and condition (
4), which is equivalent to
for any
for each
In (
57), if we use Gronwall’s inequality for any
and
, we get
where the constant
is independent of
. Thus, from (
58), it is written that
which is equivalent to
Since
by limit relation (
43), we obtain
from (
60). This shows that the sequence
converges in the norm of
. Because the space
is complete, the limit function
of
is in
, that is,
. Moreover,
satisfies the integral identity (
36). To show this, let us substitute the test function
such that
for test function
in (
47). Thus, by the formula of integration by parts, for any
and
, we get
If we take the limit of equality (
63) as
we obtain
for any
and
In (
64), taking
and using the condition
for a.a
, we prove that (
36) holds for
, that is, the limit function
is a solution of problems (
33)–(
35) in the meaning of Definition 4.
If we substitute
for the test function
in (
47), we get
by integration by parts. Subtracting its complex conjugate from (
65) and using relation (
55) for
, we obtain
which is equivalent to
by conditions (
45) and
for
In (
66), using the Cauchy–Schwarz inequality and the conditions
and (
4), we get
for any
, which implies that
by Gronwall’s inequality, where the constant
is independent of
m. Thus, if we take the limit of (
68) as
, we prove that the limit function
of
satisfies (
42), which implies that the solution of (
33)–(
35) is unique. Thus, the proof of Theorem 5 is completed. □
Since problems (
33)–(
35) and problem (
30)–(
32) are equivalent, it is easily written that
from Theorem 5, which implies that
due to the fact that
is the complex conjugate of
. Also, since
, we can easily say that problems (
15)–(
17) have a unique solution
w in
satisfying the estimate
Now, let us give the next theorem for the solution of the adjoint problem by using the solution of problems (
15)–(
17):
Theorem 6. Let the assumptions of Theorem 1 be fulfilled and be a given function. Also, let the functions satisfy conditions (3), (4), and (40). Then, problems (8)–(10) have a unique solution in . Moreover, there is a constant that does not depend on t such that Proof. We have proven above that problems (
15)–(
17) have a unique solution
w in
in the meaning of Definition 3 satisfying estimate (
71), and also, problems (
18)–(
20) have a unique solution
z in
satisfying estimate (
25). Hence, since
, we come to the conclusion that problems (
8)–(
10) have a unique solution
in
in the meaning of Definition 2. Thus, if we substitute
and
in (
26), we write
for any
Also, since
we can easily obtain the relation
by integrating by parts and using conditions (
4) and (
19). If we substitute (
74) into (
73), we get
which is equivalent to
by (
18). Then we deduce from above that
satisfies integral identity (
11), that is,
is a unique solution of problems (
8)–(
10) in
in the meaning of Definition 2. Also, since
, it is written that
from (
71). Here, if we consider the inequality
and
we easily write the inequality
which implies that
by (
25). Also, since
, we can easily say that function
provides estimate (
72), which completes the proof. □