1. Introduction
Fractional calculus is an extension of the ordinary differentiation and integration to arbitrary non-integer order. In recent years, this theory has become an important object of investigations due to its demonstrated applications in different areas of physics and engineering (see, for example, [
1,
2] and the references therein). In particular, time fractional differential equations are used when attempting to describe transport processes with long memory. Recently, the study of time fractional ordinary and partial differential equations has received great attention from many researchers, both in theory and in applications; we refer the reader to the monographs of Abbas et al. [
3,
4,
5], Samko et al. [
6], and Kilbas et al. [
7], and the papers [
8,
9,
10,
11,
12,
13,
14] and the references therein. On the other hand, the existence of solutions of initial and boundary value problems for fractional differential equations with the Hilfer fractional derivative have started to draw attention. For the related works, see for example [
1,
15,
16,
17,
18,
19,
20] and the references therein.
Functional differential equations with random effects are differential equations with a stochastic process in their vector field [
21,
22,
23,
24,
25]. They play a fundamental role in the theory of random dynamical systems.
Consider the following coupled system of Hilfer fractional differential equations:
with the following initial conditions:
where
,
is a measurable space,
are given functions,
is the left-sided mixed Riemann–Liouville integral of order
and
is the generalized Riemann–Liouville derivative (Hilfer) operator of order
and type
Next, we discuss the following coupled system of Hilfer–Hadamard fractional differential equations:
with the following initial conditions:
where
are given functions,
,
is the left-sided mixed Hadamard integral of order
and
is the Hilfer–Hadamard fractional derivative of order
and type
2. Preliminaries
We denote by
the Banach space of all continuous functions from
I into
with the supremum (uniform) norm
As usual,
denotes the space of absolutely continuous functions from
I into
By
we denote the space of Lebesgue-integrable functions
with the norm:
By
and
we denote the weighted spaces of continuous functions defined by:
with the norm:
and:
with the norm:
Furthermore, by
, we denote the product weighted space with the norm:
Now, we give some definitions and properties of fractional calculus.
Definition 1. [4,6,7] The left-sided mixed Riemann–Liouville integral of order of a function is defined by:where is the (Euler’s) Gamma function. Notice that for all
and each
we have
and:
Definition 2. [4,6,7] The Riemann–Liouville fractional derivative of order of a function is defined by: Let
and
Then, the following expression leads to the left inverse operator as follows.
Moreover, if
then the following composition is proven in [
6]:
Definition 3. [4,6,7] The Caputo fractional derivative of order of a function is defined by: In [
1], R.Hilfer studied applications of a generalized fractional operator having the Riemann–Liouville and the Caputo derivatives as specific cases (see also [
17,
19]).
Definition 4. (Hilfer derivative). Let and The Hilfer fractional derivative of order α and type β of w is defined as: Property 1. Let and
The operator
can be written as:
Moreover, the parameter
satisfies:
The generalization (
5) for
coincides with the Riemann–Liouville derivative and for
with the Caputo derivative.
If
exists and is in
then:
Furthermore, if
and
then:
If
exists and is in
then:
Corollary 1. Let Then, the Cauchy problem:has the following unique solution: Let
be the
-algebra of Borel subsets of
A mapping
is said to be measurable if for any
one has:
Definition 5. Let be the direct product of the σ-algebras and those defined in Ω and , respectively. A mapping is called jointly measurable if for any one has: Definition 6. A function is called jointly measurable if is measurable for all and is continuous for all:
A random operator is a mapping
such that
is measurable in
w for all
, and it expressed as
we also say that
is a random operator on
The random operator
on
E is called continuous (resp. compact, totally bounded, and completely continuous) if
is continuous (resp. compact, totally bounded, and completely continuous) in
u for all
The details of completely continuous random operators in Banach spaces and their properties appear in Itoh [
26].
Definition 7. [27] Let be the family of all nonempty subsets of Y and C be a mapping from Ω into A mapping is called a random operator with stochastic domain C if C is measurable (i.e., for all closed is measurable), and for all open and all is measurable. T will be called continuous if every is continuous. For a random operator a mapping is called a random (stochastic) fixed point of T if for P-almost all and , and for all open is measurable. Definition 8. A function is called random Carathéodory if the following conditions are satisfied:
- (i)
The map is jointly measurable for all and
- (ii)
The map is continuous for all and
Let with
By , we mean Also and If then means
Definition 9. Let X be a nonempty set. By a vector-valued metric on X, we mean a map with the following properties:
- (i)
for all and if then
- (ii)
for all
- (iii)
for all
We call the pair a generalized metric space with
Notice that
d is a generalized metric space on
X if and only if
are metrics on
For
and
we will denote by:
the open ball centered in
with radius
r and:
the closed ball centered in
with radius
We mention that for generalized metric spaces, the notations of open, closed, compact, convex sets, convergence, and Cauchy sequence are similar to those in usual metric spaces.
Definition 10. [28,29] A square matrix of real numbers is said to be convergent to zero if and only if its spectral radius is strictly less than one. In other words, this means that all the eigenvalues of M are in the open unit disc, i.e., for every with where I denotes the unit matrix of Example 1. The matrix defined by:converges to zero in the following cases: - (1)
, and
- (2)
, and
- (3)
, and
In the sequel, we will make use of the following random fixed point theorems:
Theorem 1. [23,24,25] Let be a measurable space, X a real separable generalized Banach space, and a continuous random operator, and let be a random variable matrix such that for every the matrix converges to zero and:then there exists a random variable that is the unique random fixed point of Theorem 2. [23,24,25] Let be a measurable space, X be a real separable generalized Banach space, and be a completely continuous random operator. Then, either: - (i)
the random equation has a random solution, i.e., there is a measurable function such that for all or
- (ii)
the set is unbounded for some measurable function with on
Furthermore, we will use the following Gronwall lemma:
Lemma 1. [23] Let be a real function and a nonnegative, locally-integrable function on Assume that there exist constants and such that:then, there exists a constant such that:for every 3. Coupled Hilfer Fractional Differential Systems
In this section, we are concerned with the existence and uniqueness results of the system (
1) and (
2).
Definition 11. By a solution of the problem (1) and (2), we mean coupled measurable functions , which satisfy the Equation (1) on and the conditions and The following hypotheses will be used in the sequel.
The functions are Carathéodory.
There exist measurable functions
such that:
There exist measurable functions
such that:
First, we prove an existence and uniqueness result for the coupled system (
1)–(
2) by using Banach’s random fixed point theorem in generalized Banach spaces.
Theorem 3. Assume that the hypotheses and hold. If for every the matrix:converges to zero, then the coupled system (1) and (2) has a unique random solution. Proof. Define the operators
and
by:
and:
Consider the operator
defined by:
Clearly, the fixed points of the operator
N are random solutions of the system (
1) and (
2).
Let us show that
N is a random operator on
Since
are Carathéodory functions, then
are measurable maps. We concluded that the maps:
are measurable. As a result,
N is a random operator on
into
We show that
N satisfies all conditions of Theorem 1.
For any
and each
, and
we have:
Furthermore, for any
and each
, and
we get:
Since for every
the matrix
converges to zero, then Theorem 1 implies that the operator
N has a unique fixed point, which is a random solution of system (
1) and (
2). □
Now, we prove an existence result for the coupled system (
1) and (
2) by using the random nonlinear alternative of the Leray–Schauder type in generalized Banach space.
Theorem 4. Assume that the hypotheses and hold. Then, the coupled system (1) and (2) has at least one random solution. Proof. We show that the operator
defined in (
8) satisfies all conditions of Theorem 2. The proof will be given in four steps.
Step 1.is continuous.
Let
be a sequence such that
as
For any
and each
we have:
Since
is Carathéodory, we have:
On the other hand, for any
and each
we obtain:
Furthermore, from the fact that
is Carathéodory, we get:
Hence, is continuous.
Step 2. maps bounded sets into bounded sets in
For any
and each
and
we have:
Furthermore, for any
and each
and
we get:
Step 3. maps bounded sets into equicontinuous sets in
Let
be the ball defined in Step 2. For each
with
and any
and
we have:
As a consequence of Steps 1–3, with the Arzela–Ascoli theorem, we conclude that maps into a precompact set in
Step 4. The set consisting of such that for some measurable function is bounded in
Let
such that
Then,
and
Thus, for any
and each
we have:
Lemma 1 implies that there exists
such that:
This shows that the set
is bounded. As a consequence of Steps 1–4 together with Theorem 2, we can conclude that
N has at least one fixed point in
, which is a solution for the system (
1) and (
2). □
4. Coupled Hilfer–Hadamard Fractional Differential Systems
Now, we are concerned with the coupled system (
3) and (
4). Set
and denote the weighted space of continuous functions defined by:
with the norm:
Furthermore, by
, we denote the product weighted space with the norm:
Let us recall some definitions and properties of Hadamard fractional integration and differentiation. We refer to [
7] for a more detailed analysis.
Definition 12. [7] (Hadamard fractional integral) The Hadamard fractional integral of order for a function is defined as:provided the integral exists. Example 2. Let Let , Then: Definition 13. [7] The Hadamard fractional derivative of order applied to the function is defined as: In particular, if
then:
Example 3. Let Let , Then: It has been proven (see, e.g., Kilbas [
30], Theorem 4.8) that in the space
the Hadamard fractional derivative is the left-inverse operator to the Hadamard fractional integral, i.e.:
From [
7], we have:
The Caputo–Hadamard fractional derivative is defined in the following way:
Definition 14. The Caputo–Hadamard fractional derivative of order applied to the function is defined as: In particular, if
then:
Definition 15. Let and The Hilfer–Hadamard fractional derivative of order α and type β applied to the function w is defined as: This new fractional derivative (
9) may be viewed as interpolating the Hadamard fractional derivative and the Caputo–Hadamard fractional derivative. Indeed, for
, this derivative reduces to the Hadamard fractional derivative, and when
we recover the Caputo–Hadamard fractional derivative.
From [
31], we conclude the following lemma.
Lemma 2. Let be such that for any Then, Problem (3) is equivalent to the following Volterra integral equation: Definition 16. By a random solution of the coupled system (3) and (4), we mean a coupled measurable function that satisfies the conditions (4) and Equation (3) on Now, we give (without proof) similar existence and uniqueness results for the system (
3) and (
4). Let us introduce the following hypotheses:
The functions are Carathéodory.
There exist measurable functions
such that:
There exist measurable functions
such that:
Theorem 5. Assume that the hypotheses and hold. If for every the matrix:converges to zero, then the coupled system (3) and (4) has a unique random solution. Theorem 6. Assume that the hypotheses and hold. Then, the coupled system (3) and (4) has at at least a random solution.