1. Introduction
Due to their widespread applications in numerous significant applied fields, including diffusion theory, electromagnetism, population dynamics, fluid dynamics, seepage flow in porous media, heat conduction in materials with memory, autonomous mobile robots, and traffic models, fractional differential equations (FDEs) have drawn a lot of attention. Classical theory and applications of FDEs are discussed in the novels [
1,
2,
3,
4,
5,
6] and papers [
7,
8,
9,
10]. Hilfer [
11] introduced a fractional derivative, which is a generalization of both R–L and the Caputo fractional derivatives, known as the Hilfer fractional derivative (HFD). Some authors [
12,
13,
14,
15,
16] examined the existence of mild solution results of FDEs by utilizing HFD. Recently, the researcher in [
17] investigated the HF neutral stochastic differential equations (SDEs) with NII by employing the Mönch fixed-point method.
The mathematical control theory includes the notion of controllability. A dynamical system is said to be controllable if it can be guided, by the set of admissible inputs, from an arbitrary initial state to an arbitrary final state. Several writers have explored controllability difficulties for various types of dynamical systems (see [
18,
19,
20,
21,
22,
23]) and the references therein. The researcher Wang et al. [
24] established the controllability of Hilfer fractional NII semilinear differential inclusions with nonlocal conditions. Recently, the researchers [
25] investigated the controllability of nonlocal HF delay dynamic inclusions with NII and a non-dense domain.
Since noise and fluctuating systems are frequent and inherent in both artificial and natural systems, stochastic models ought to be investigated rather than deterministic ones. SDEs capture some occurrences in a way that makes them mathematically unpredictable. For an extensive overview of SDEs and their uses, one can refer to [
26,
27,
28,
29,
30,
31]. All physical systems evolving with respect to time experience abrupt changes called impulses. These impulses can be split into two distinct types: (i) instantaneous impulses and (ii) non-instantaneous impulses (NII). In a system, impulse occurs for a short time period, which is negligible when comparing the overall time period with an instantaneous impulse. Impulsive disturbance, which starts at any time and remains active over a finite time period is a non-instantaneous impulse. These NII are observed in lasers and in the intravenous introduction of drugs into the bloodstream. In 2016, Gautam and Dabas [
32] established mild solutions for a class of neutral fractional functional differential equations with NII. Nowadays, most researchers [
18,
21,
24,
30,
33,
34,
35,
36] study non-instantaneous impulses with the HFD. Researchers delve into the study of non-densely defined operators to tackle the complexities of control and ensure the efficient operation of a wide range of systems, from robotics and autonomous vehicles to power grids and biological networks [
9,
10,
14,
19,
22,
25]. As far as we are aware, no research has been published on the subject of controllability in NII HF neutral stochastic evolution equations with a non-dense domain.
Consider the controllability of NII HF neutral stochastic evolution equations with a non-dense domain:
where
stands for the HFD of order
and type
. Here
, and
represent the time intervals. The fixed points
and
satisfy
. The operator
is a non-densely closed linear operator and generates an integrated semigroup
in Hilbert space (HS)
with
and
. The control function
is provided in
, an HS of admissible control function with
an HS,
is the appropriate function. Let
be another distinct HS with
and
.
The primary contributions of this article are as follows:
This manuscript focuses on the controllability of NII HF neutral stochastic evolution equations with a non-dense domain.
To show the relatively compact requirements, the Hausdorff measure of noncompactness (MNC) is used.
The main result is motivated in abstract space by applying the theory of fractional calculus, semigroup operators, and methods based on the fixed-point theorem.
The discussion is driven by some suitable assumptions, including the Hille–Yosida condition without the compactness of the semigroup of the linear part.
An illustration has been provided to demonstrate the efficiency of the obtained findings.
The structure of our article is as follows: A few key conclusions and terminology related to the fixed-point theorem, stochastic analysis, semigroup theory, and fractional calculus are found in
Section 2. We develop the controllability results in
Section 3. Lastly, an example demonstrating the established results is provided in
Section 4.
2. Preliminaries
In this section, we introduce some fundamental terminology, definitions, and some earlier results that are used in this manuscript.
The symbols and represent the two real HS. Consider the complete probability space connected to an entire set of right continuous increasing sub -algebra such that . Consider a Q-Wiener process , identified on , with the covariance operator Q such that . is the set of all square-integrable, strongly measurable -valued arbitrary components with a Banach space connected with , which is equal to .
The space of all bounded linear operators from
, whenever
, is defined by
, which is represented by
. One may express a non-negative self-adjoint operator as
. Let
be the space of all Hilbert-Schmidt operators from
,
, which is said to be a
Q-Hilbert–Schmidt operator. For
and
, consider the weighted spaces of continuous functions
Now, we specify
is a Banach space
Let
. Let
and
exists,
, with
Now, we introduce some assumptions for further analysis:
- (A1)
fulfils the Hille–Yosida presumption, i.e., there exists
and
such that
and
Set
. Assume
to be a part of
in
classified as
,
as the domain of
. Subsequently, by referring to [
4], the component
of
represents a strongly continuous semigroup
on
with
, where
M and
v are constants. Describe
.
Assume with I, the identity operator on , then for any , we obtain as and . Assume , then . Describe equipped with . Undoubtedly, is a HS. Note for and iff .
The Wright function is explained as follows
which fulfils
Definition 1. [17,24] An -adapted stochastic process is called a mild solution of the system (1)–(3) if the succeeding integral equation is fulfilled:where Lemma 1. - (i)
is continuous in the uniform operator topology for .
- (ii)
and are strongly continuous for .
- (iii)
For the linear operators and , and for every , we obtain
Now, we introduce the definition and some basic characteristics of Hausdorff MNC [
37,
38].
Definition 2. [39] The Hausdorff MNC μ of the set in the HS is specified asfor each bounded subset in the HS . Definition 3. [37] A continuous and bounded map is said to be μ-contraction if there exists a constant such thatfor every noncompact bounded subset , where is a Banach space. Lemma 2. [37] If is a series of Bochner integrable functions with the measurement , for all and for , where , then the function in and fulfils Lemma 3. [37] Let be a bounded set; then, a countable set exists such that . Definition 4. [24] System (1)–(3) is said to be controllable on the interval if for each , there exists a control function such that any corresponding mild solution of for the system (1)–(3) must satisfy the condition and Theorem 1. (Darbo–Sadovskii) [37] If be closed, bounded and convex. If the continuous map is a μ-contraction, then Ψ
has a fixed-point in . 3. Controllability
In this section, we will demonstrate the existence result, which is based on the Darbo–Sadovskii fixed-point method; for this, we have the succeeding presumptions:
- (H1)
The operator in such that where, is a constant.
- (H2)
- (a)
The function
is continuous and there exists constants
for all
,
- (b)
There exists a function
and
with
such that for each bounded subset
,
- (H3)
The function satisfies
- (a)
is continuous for a.e , and is strongly measurable for .
- (b)
There exists a function
and a continuous increasing function
such that for every
and
,
- (c)
There exists a function
and
with
such that for every bounded subset
,
- (H4)
The functions are continuous and fulfil the preceding requirements:
- (a)
For
, there exists positive functions
dependent on
such that
- (b)
There exists constants
such that for any bounded subset
,
- (H5)
- (a)
The function is bounded, represented by , and it has an inverse operator , and there exist two positive constants and such that .
- (b)
There exists a function
and
with
such that for each bounded subset
,
Theorem 2. If - holds, then the noninstantaneous impulsive HF neutral stochastic evolution of Equations (1)–(3) has a mild solution on . Proof. Depending on hypothesis
, we can define the control function
, as follows:
Using this control, we will show that the operator
is defined by:
Let us show that using the control function defined by (4), any fixed point for
is a mild solution for (
1)–(3) and satisfies
and
. Infact, if
is a fixed point for
, then from (4), we have
We now prove, using Theorem 1, that
has a fixed point.
Indeed, it is enough to demonstrate for every , there exists such that for , we have .
For
,
By Lemma 1, we have
According to Lemma 1 and
, we obtain
According to Lemma 1 and
, we have
By using Lemma 1 and
, we obtain
From the above, (
5) becomes,
Next, for
Similarly, for every
one can estimate,
Let
then for any
, we obtain
.
Let
with
in
. Therefore, the continuous functions are
and
for every
, and there exists
such that for any
,
For each
, we obtain
By
Lebesgue Dominated Convergence Theorem, for
,
Next, for every
For any
Then,
Therefore,
is continuous.
Let
. For every
,
For
,
Similarly, for
,
The RHS of the aforementioned inequalities → 0 as
, and since the operators
are continuous, we obtain that
independently of
as
, for
sufficiently small. Moreover,
is equicontinuous. Thus,
maps
into a set of equicontinuous.
Let
, then by Lemma 3, there exists a countable set
such that
. By the equicontinuousness of
, we know that
is also equicontinuous. Then, by Lemma 3, we have
Now, define
Let
.
First, we estimate
, for
, and we obtain
Since,
is relatively compact, we obtain
where
For
we obtain
where
.
For
we obtain
where
Thus, by Definition 1,
is a
-contraction operator. Hence,
has at least one fixed-point from Theorem 1, and the mild solution also exists.
4. Examples
4.1. Example I
Consider the partial Hilfer fractional derivative system,
where
is the HFD of order
. Let
be a one-dimensional standard Brownian motion in
represented by
on the filtered probability space
. Consider
equipped with the uniform topology, and let the operator
be classified by
Then, we have
As we know from [
40],
fulfils the Hille–Yosida condition with
and for
,
. Also, if
is taken for
, by Hille–Yosida condition,
produces a
-semigroup
, which is evidenced by
where
is a complete orthonormal basis in
. Clearly,
.
Now, define an infinite dimensional space
by
We shall define a norm in
by
.
Define a mapping
as follows:
Obviously,
Now, we represent the system (
6) in the abstract form (
1)–(3) by setting
Then, for any bounded set
, we estimate
Also, it is easy to verify that,
Hence, we have that the functions
satisfy the hypotheses
. Further, we assume that the linear operator
defined by
admits an invertible operator and satisfies
.
Hence, all the requirements of Theorem 2 are fulfilled. Therefore, system (
6) has at least one mild solution. Furthermore, system (
6) can be steered from the initial state
to the final state
. Thus, system (
6) is controllable.
4.2. Example II
Consider the following partial non-instantaneous impulsive Hilfer fractional neutral stochastic evolution system of the form
where
is the HFD of order
. Let
be a one-dimensional standard Brownian motion in
represented by
on the filtered probability space
. Consider
equipped with the uniform topology and the operator
to be classified by
Then, we have
We know from [
40] that
fulfils the Hille–Yosida condition with
and for
,
. Also, if
is taken for
, by Hille–Yosida condition,
produces a
-semigroup
, which is evidenced by
where
is a complete orthonormal basis in
.
Clearly, .
Now, define an infinite dimensional space
by
We shall define a norm in
by
.
Define a mapping
as follows:
Now,
is any bounded subset
. Define
Hence, we have that the functions
satisfy the hypothesis
. Further, we assume that the linear operator
defined by
admits an invertible operator and satisfies
.
Hence, all the requirements of Theorem 2 are fulfilled. Therefore, system (
7) has at least one mild solution. Furthermore, system (
7) can be steered from the initial state
to the final state
. Thus, system (
7) is controllable.
5. Conclusions
This manuscript deals with the controllability results for NII HF neutral stochastic evolution equations, which are defined in the non-dense domain. The primary outcomes are obtained by employing semigroup theory, fractional calculus, stochastic analysis, and the fixed-point theorem. At the end, we provided an illustration to explain our results. In the future, we will investigate the optimal control of the Sobolev-type hemivariational stochastic HF NII differential system with Poisson jumps and a non-dense domain.
Author Contributions
Conceptualisation, G.G., R.U., S.S., S.V. and B.A.; methodology, G.G. and S.S.; validation, G.G. and R.U.; formal analysis, S.S.; investigation, R.U., B.A. and S.S.; resources, R.U.; writing—original draft preparation, S.S.; writing—review and editing, R.U., S.V. and B.A.; visualization, S.S. and R.U.; supervision, R.U.; project administration, R.U., S.V., S.S. and B.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
Acknowledgments
The authors thank the referees very much for their valuable advice on this paper.
Conflicts of Interest
The authors declare no conflicts of interest.
Abbreviations
The following abbreviations are used in this manuscript:
FDEs | Fractional differential equations |
R-L | Riemann–Liouville |
HF | Hilfer fractional |
HFD | Hilfer fractional derivative |
SDEs | stochastic differential equations |
NII | non-instantaneous impulse |
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