1. Introduction
In recent decades, fractional calculus theory has proven to be a significant tool for the formulation of several problems in science and engineering, where fractional derivatives and integrals can be utilized to describe the characteristics of various real materials in various scientific disciplines; see, e.g., [
1,
2,
3,
4,
5]. This theory has recently received a large amount of consideration by many academics; we mention Euler, Laplace, Riemann, Liouville, Marchaud, Riesz, and Hilfer; see, e.g., [
6,
7,
8]. Distributed parameter systems can be analysed in terms of controllability, observability, and stability, which lead to numerous applications. However, one of the most basic concerns in system analysis and control is observability, which is concerned with the reconstruction of a system’s initial state that is taken from measurements on a system by means of so-called sensors; see, [
9]. Amouroux et al. [
10] developed two approaches to investigate regional observability (ReOb) for distributed systems. The first is state-space-based, and the second allows for estimating the state on the considered subregion. El Jai et al. [
11] introduced the concept of regional strategic sensors for a class of distributed systems and presented the sensor characterization for various geometrical situations. In [
12], Al-Saphory et al. considered and analysed the notion of regional gradient strategic sensors, and the results applied to a two-dimensional linear infinite distributed system in Hilbert space.
In a problem governed by a diffusion system, it is commonly known that the positioning of sensors is restricted by severe practical restrictions. In fact, observation processes are generally restricted to subsets, boundaries, or points [
13,
14]. This indicates that the operators of the observation can be unbounded in their state spaces.
Recently, the study of ReOb for partial differential equations (PDEs) has received considerable attention in the literature. Zerrik et al. [
15] reviewed regional boundary observability for a two-dimensional diffusion system. In [
16], Chen investigated infinite time exact observability for the Volterra system in Hilbert spaces. Chen and Yi [
17] studied the observability and admissibility of Volterra systems in Hilbert spaces. Zouiten et al. [
18] studied the following ReEnOb for a linear parabolic system.
where
A is an infinitesimal operator and generates a strongly continuous semigroup
on the state space
,
is an open bound of
, and
is the output function (OuPuFu), which represents the measurements. The authors used the HUM approach to reconstruct the initial state between two profiles in an internal subregion.
More recently, many researchers have investigated the ReOb for fractional differential equations (FDEs). In [
19], Zguaid and El Alaoui investigated the notion of the regional boundary observability of Caputo fractional systems. Zguaid et al. [
20] studied ReOb for a class of linear time-fractional systems using the HUM approach and proved that the considered approach allows to transform the ReOb problem into a solvability one. Regional gradient observability for Caputo fractional diffusion systems is considered in [
21]. In [
22], Ge et al. presented the notion of the regional gradient observability for Riemann–Liouville (R-L) diffusion systems for the first time. Cai et al. [
23] investigated the concept of exact and approximate ReOb of Hadamard–Caputo diffusion systems using the HUM approach. Zguaid and El Alaoui [
24] investigated the notion of regional boundary observability of R-L linear diffusion systems by using an extension of HUM.
On the other hand, some works concerning the concept of ReEnOb-FDEs have recently been conducted. In [
25], Zouiten et al. studied the ReEnOb for R-L fractional evolution equations with R-L derivatives:
where
is an open bound of
, with the regular boundary
and
and
are R-L fractional derivatives and R-L fractional integrals of orders
and
, respectively. The authors developed an approach based on HUM allowing them to reconstruct the initial state between two given functions in an internal subregion of the whole domain. In [
26], Zouiten and Boutoulout investigated the ReEnOb for the following Caputo fractional diffusion system in a Hilbert space
The HUM approach for fractional differential systems is used for the process of reconstructing the initial state between two profiles in a considered subregion of the whole domain.
Inspired and motivated by the above discussion, in this manuscript we extend the investigation of the notion of the ReEnOb for sub-diffusion systems with fractional derivatives, augmented and restricted by some measurements given by the so-called OuPuFu. We note that FDEs have been widely used for modelling in various science and engineering fields due to their well-described systems and high accuracy, as well as yielding better results compared with systems with integer differentiation. Therefore, the results obtained from Systems (
2) and (
3) are better than those of System (
1). Moreover, use the Hilfer fractional derivative as we know it has two parameters and contains Caputo and R-L derivatives in its definition. Thus, our findings can be seen as a generalization of the mentioned results.
This paper is interested in the concept of ReEnOb for the following sub-diffusion system via Hilfer FDs of order
, type
and augmented with the OuPuFu (
5). We first characterize the ReEnOb of a diffusion system augmented with the OuPuFu in an internal subregion
of
. Moreover, we recognize two types of sensors based on the boundness issue of the observation operator
C. Then, we reconstruct the initial state
of the addressed system using an approach that relies on the HUM approach introduced by Lions [
27]. The investigation of the addressed problem shows that it is possible to obtain the desired state between two profiles in some selective internal subregions. Let
be an open bound of
with the regular boundary
, and let
. The space
and
. We consider the following diffusion sub-system:
where
stands for the Hilfer fractional derivative (left-sided) of order
, type
with respect to time
t, the integral
,
,
is the left-sided R-L fractional integral operator (1), and the operator
A is linear and has a dense domain, so the coefficients are independent of time
t. Moreover, operator
A is infinitesimal and generates a strongly continuous semigroup
on the state space
, which is a Hilbert space. Here, the initial state
is assumed to be unknown. The measurements and information of System (
4) are obtained by the OuPuFu below:
where
C is the observation operator, and it is a linear, not necessary a bounded, operator determined by the number of sensors or their structure, with a dense domain
with range in the observation space
is the number of considered sensors), and
is a Hilbert space.
This paper is arranged as follows: In
Section 2, we review the definitions, basic concepts, and lemmas utilized throughout this paper. In
Section 3, we characterize the ReEnOb. Moreover, we present some remarks, then introduce and prove the main theorem of the ReOb of the Hilfer diffusion System (
4). In
Section 4, the HUM approach is introduced and applied in the reconstruction process of the initial state of System (
4). In addition, two theoretical illustrative examples are given to support our results. In
Section 5, we give some conclusions.
2. Preliminaries
In this section, we review the essential definitions, notations, and basic facts utilized throughout this paper.
Definition 1. (See [7]) The R-L fractional integral (left-sided) of order η for a function is defined as Definition 2. (See [7]) The R-L fractional integral (right-sided) of order η for a function is defined as Definition 3. (See [1,28]) The R-L fractional derivative (left-sided) and R-L fractional derivative (right-sided) of order with respect to t for a function f are defined asandrespectively, where the notation stands for differentiation. Definition 4. (See [1,28]) The Hilfer fractional derivative (left-sided) and the Hilfer fractional derivative (right-sided) of order , type with respect to t for a function f are respectively defined byfor almost everywhere , where , , , and . Next, we recall a mild solution for the following Hilfer fractional evolution equation; see [
29].
Lemma 1. Let be a Hilbert space, for any , , and , the function is said to be a mild solution of the following systemif u fulfilswhere , and the function where , is the Wright function, which fulfils the following equality: Remark 1. (See Remark 2.14 in [29]) Let , , and ; thus, we havewhereand We can rewrite the equality in (
7) as follows:
Note that if the non-linear term of System (
6) is zero, then the mild solution (
11) becomes
. Consequently, the mild solution of (
4) may alternatively be expressed as
We give the following lemma, which will be utilized afterwards to prove our results.
Lemma 2. (See [30]) Let a function g be defined on interval , and , then the reflection operator acting on g is Lemma 3. Let f be a function defined on the interval and let f be differentiable and integrable in the Hilfer derivative sense. We now introduce the reflection operator when acting on f as follows: Moreover, the following assertions hold,
- (i)
.
- (ii)
.
- (iii)
.
- (iv)
.
Note that, assertions (i) and (ii) are given in [25,26]. Here, we state their proof due to the demonstration of assertions (iii) and (iv). Proof. Our proof is obtained by virtue of Equation (
13) and by utilizing changes in the variables, specifically, changes in the role of time.
(i): We show that
. Since
Using the change in the variables, let
, then
. Now, for
and
, we obtain
and
, respectively. Let us fix
. Substituting these values into (
14), we obtain
Let
, we obtain
We now consider the right-hand side:
Consequently, from (
15) and (
16), we can see that
.
(ii): The proof follows the same way as (i). Considering the left-hand side:
and the right-hand side:
(iii): We demonstrate
. Let us fix
, which will be used in the remainder of the proof of this lemma. We first consider the left-hand side:
Let
, then
. Now, for
and
, we obtain
and
, respectively. Substituting these values into (
17), we obtain
Let
, then
. Now for
and
, we obtain
and
, respectively. Substituting these values into (
18), we obtain
Let
and
, we obtain
On the other hand, we proceed with the right-hand side as follows:
Hence, .
(iv): The proof follows the same way as (iii). We first consider the left-hand side:
then the right-hand side:
Consequently, .
Thus, this completes the proof of the lemma. □
Since
C is an admissible operator, as we will see later, then the OuPuFu of System (
4) is given by
where
is a fractional linear operator. Let us recall the observation space
. Two cases arise for obtaining the adjoint operator of
.
Case 1.
C is bounded. In this case, we can define zonal sensors. Let operator
C be from
to
. Then, if
is adjoint on the other hand, the adjoint of operator
can be obtained by
Case 2.
C is unbounded. We can define pointwise sensors. However, in this case, the operator
C can be introduced from
to the observation space
. Then,
is adjoint. However, in order to give this case a sense of (
5), we make an assumption on
C in the following definition, namely,
C is an admissible observation operator, as we will see in Definition 5 below.
Definition 5. (See [18]) The observation operator C is an admissible of (4) and (5), if for any there is a constant , such that Note that operator
C being admissible assures that the map
can be extended to a bounded linear operator from
to the space
. Thus, we can introduce
as the adjoint of operator
as follows:
3. Characterization of Enlarged Observability
In this section, we will characterize the ReEnOb of System (
4) with the output function (
5) in the subregion
of
. Let
be a positive Lebesgue measure, and let us define the restriction mapping (projection mapping)
, as follows:
We can now define the adjoint
of
as follows:
when
, and
when
. In addition, we note that the regional exact observability of System (
4) with (
5) can be achieved at time
t in the subregion
, if
, see, e.g., [
25,
26,
31,
32,
33]. Now, let
and
,
almost everywhere in the subregion
, be two functions defined in
. We thus define the following set
where
and
are given functions in
. We assume that the initial state is given by
The main objective of the investigation proposed in this paper is to demonstrate ReEnOb for Hilfer time fractional-order diffusion systems, that is, we will answer the following question: Given the Hilfer fractional diffusion System (
4) with (
5) in the subregion
at time
, can we reconstruct
between
and
?
The following definition will be used in the following.
Definition 6. If , then System (4) with (5) is exactly -observable in the subregion ω. Definition 7. A sensor is exactly -strategic in the subregion ω if the observed system is exactly -observable in subregion ω.
The following three remarks show that the results obtained in [
18,
25,
26] are particular cases of our results.
Remark 2. If and , then the Hilfer fractional diffusion (4) corresponds to the normal diffusion process, which is investigated in [18]. Remark 3. If and , then the Hilfer fractional diffusion System (4) corresponds to the R-L fractional diffusion process, which is investigated in [25]. Remark 4. If and , then the Hilfer fractional diffusion (4) corresponds to the Caputo fractional diffusion process, which is considered in [26]. The following result can be obtained directly from Definition 7.
Remark 5. If System (4) with the OuPuFu (5) is exactly -observable in , then for any subregion of it is also exactly -observable in . The following remark will be used in the proof of the theorem presented below.
Remark 6. Let X be a Hilbert space and F a linear subspace of X, then , where is the orthogonal complement of F.
Theorem 1. The following assertions are equivalent:
- 1.
System (4) with the OuPuFu (5) is exactly -observable in the subregion ω. - 2.
.
Proof. We show that Statement 1 implies Statement 2, and Statement 2 implies Statement 1. The following two facts play a key role in the proof.
it follows from Remark 6 that
We demonstrate that the left-hand side implies the right-hand side, and vice versa:
Let
, then
. From (
20), one can see that
. Therefore, it follows from (
21) that,
has at least one element, which is zero. Thus,
.
We now prove that statement 2 implies statement 1, that is,
Now, let
, then
,
and
. From (
20) and (
21), we have
and
, respectively. Consequently, one can see that
therefore,
which contradicts (
22). Thus, (
23) is not true. Consequently,
Therefore, System (
4) with (
5) is exactly
-observable in the subregion
. This completes the proof. □