1. Introduction
The Riemann–Liouville fractional integral
of order
is defined for the function
H [
1,
2] as
It follows that
The Liouville–Caputo fractional derivative
of order
of the function
H is defined as [
1]
It follows that
The set
is a Banach space of all continuous functions from
into
with the norm
Let
and
be a functional. The purpose of the current work is to investigate the uniqueness, existence, and stability for the following new equation with variable coefficients for
:
where
and
F are mappings from
into
with certain conditions.
In addition, we aim to find a new series solution to a Caputo fractional convection equation (PDE) in with an initial condition based on the inverse operator method at the end to show an application of the inverse operator method in fractional PDEs.
The two-parameter Mittag–Leffler function [
3] is defined by
where
.
To demonstrate the use of the functional inverse operator approach, we first consider the following simpler version of Equation (
1) for
and
:
where
is a constant and
F is a continuous function on
with
We should point out that
is nonlocal because it ties the value at
to an integral over the entire domain. Generally speaking, it appears in problems involving global feedback, delayed responses, or non-instantaneous initialization, such as heat flow with memory, ecological systems with global resource limits, and models where sensors average data over a range before feedback.
Applying
to Equation (
2), we come to
by noting that
Hence,
To use the inverse operator method, we first define the functional operator
over the space
as
Then,
is well-defined in
. Since, for any
, we have
Thus,
is continuous over
and the series
is uniformly convergent. We further prove that
is an inverse operator of
, namely
Clearly,
Moreover,
is unique. In fact, assume
is another operator satisfying
Then, we derive
by applying
to the above.
From Equation (
3), we get
which is equivalent to Equation (
2) and
by noting that
.
By Banach’s fixed-point theorem and the Mittag–Leffler function given above, we can use the implicit integral Equation (
4) to find sufficient conditions for the uniqueness of Equation (
2). To do so, we define a mapping
over
as
Then,
Thus,
is a mapping from
to itself.
Furthermore, we suppose that
F satisfies the following Lipschitz condition for a constant
:
and
Then, there is a unique solution in
to Equation (
2). We only need to show that
is contractive. Clearly,
Therefore,
by noting that
Since
, by Banach’s contractive principle, there exists a unique solution in
to Equation (
2).
In summary, we have the following result:
Theorem 1. Let , and ω be a constant. We further assume that is a continuous and bounded function over with the condition for a constant :andThen, there is a unique solution in to Equation (2). Example 1. The equation with a nonlocal initial conditionhas a unique solution in . Proof. From the equation, we get
and
is continuous and bounded over
and satisfies
which claims that
. From Theorem 1, we need to find the following value of
:
using an online calculator from Wolfram Mathematica. Therefore, there is a unique solution. □
Stability is a key topic in differential equations [
4]. Stability of a differential equation generally refers to how solutions behave over time in response to (a) initial conditions, and (b) perturbations (small changes in data, inputs, or forcing terms). There are different types of stability depending on context. Our stability concept is to study solutions that do not blow up due to small errors. The idea of such stability is the substitution of a differential equation with a given inequality that acts like a perturbation of the differential equation.
Definition 1. Equation (1) is stable if there is a constant , such that, for all and for each fixed solution ofand then there exists a solution of Equation (1), satisfyingwhere Λ is a stability constant, which is independent of ϵ. Clearly, it is not unique. Fractional differential equations are critical because they provide a more accurate and flexible framework for modeling real-world phenomena that exhibit memory, nonlocality, and anomalous behavior—features that classical (integer-order) differential equations cannot capture effectively. In many physical, biological, and engineering systems, the current state depends not only on the present but also on the entire history of the system. Fractional derivatives naturally incorporate memory due to their integral-based definitions (nonlocal properties). There are many interesting studies on fractional differential or integral equations due to their strong demands and applications in various pure and applied fields [
5,
6]. Metzler et al. [
7] used fractional relaxation regarding filled polymer networks and investigated the dependence of the decisive occurring parameters on the filler content. Momani and Odibat [
8] implemented analytical techniques, the variational iteration method and the Adomian decomposition method, for solving linear fractional partial differential equations arising in fluid mechanics. Dehghan and Shakeri [
9] presented the solution of ordinary differential equations with multi-point boundary value conditions by means of a semi-numerical approach, which is based on the homotopy analysis method, with engineering applications. In 2021, Li [
10] studied the uniqueness of solutions for certain partial integro-differential equations with the initial conditions in a Banach space using the inverse operator approach, convolution, and Banach’s contractive principle. Xu et al. [
11] employed the local fractional variational iteration method to obtain approximate analytical solution of the two-dimensional diffusion equation in fractal heat transfer with help of local fractional derivative and integral operators. In 2014, Cabada and Hamdi [
12] studied the existence of solutions of the following nonlinear fractional differential equations with integral boundary value conditions:
where
and
and
is the Riemann–Liouville fractional derivative of order
.
In 2018, Zhu [
13] investigated the existence and uniqueness of the following equation using the Henry–Gronwall integral inequalities:
Equation (
1) is essentially important because it represents a new generalized fractional integro-differential boundary value problem that incorporates several key features found in complex real-world systems:
(a) It involves both a Caputo fractional derivative and fractional integrals as well as , which model memory effects and nonlocal behavior—critical in fields such as viscoelasticity, control theory, and diffusion processes.
(b) The presence of nonlinear functions and makes this equation more realistic for modeling physical and biological systems, where responses often depend nonlinearly on states or inputs.
(c) The variable coefficient introduces inhomogeneity, allowing the model to adapt to position-dependent properties or processes—important in heterogeneous media or materials with spatial variation.
(d) The boundary conditions are non-standard: At , the value depends on an integral condition involving . At , it depends on a functional , which could be nonlocal, nonlinear, or global in nature. These types of boundary conditions arise naturally in population dynamics, thermodynamics, economics, and fluid mechanics, where the state at a boundary is governed by average or cumulative behavior.
(e) From a theoretical perspective, studying existence, uniqueness, and stability for such an equation is nontrivial due to the combination of fractional operators, nonlinear terms, functional boundary conditions, and a mixed initial-boundary structure.
The motivation for employing the inverse operator method and Mittag–Leffler functions in the present work stems from the fact that, to the best of our knowledge, there are no existing integral transforms or alternative approaches capable of converting Equation (
1) into an equivalent integral equation. However, to apply fixed-point theory for studying uniqueness and existence, such an equivalent integral formulation is essential in order to define a suitable nonlinear operator.
In the following sections, we derive an implicit integral equation that is equivalent to Equation (
1). Then, by Banach’s contractive principle, a functional inverse operator, as well as the Mittag–Leffler function, we will obtain sufficient conditions for the uniqueness and stability. Furthermore, we study the existence based on Leray–Schauder’s fixed-point theorem. Also included are illustrative examples demonstrating applications of the main theorems. At the end, we find a series solution to a time-fractional convection equation in
to show an application of the inverse operator method in PDEs.
4. An Application
To complete this paper, we are going to provide a series solution to the following important Caputo fractional convection equation in
for
to demonstrate applications of inverse operators in PDEs:
where
,
for
and
This equation with the initial condition is vital in applications based on the following factors:
(a) for introduces memory effects into the evolution of the system. This is crucial for accurately modeling anomalous transport, subdiffusion, and history-dependent processes. Classical convection equations (with integer derivatives) assume that the system’s rate of change depends only on the present, while this model assumes dependence on the entire history of the system.
(b) When
, the equation reduces to the classical convection (or transport) equation:
which is widely used in fluid mechanics, traffic flow, and wave propagation.
(c) For , the equation captures subdiffusive dynamics, making it suitable for systems where transport is slower than classical models predict, such as in porous media, biological tissues, or financial markets.
(d) The term
represents convection or directional transport, which appears in heat transfer, fluid flow, and atmospheric dynamics.
To begin our process, we define the partial fractional integral
of order
as
Then, apply
to Equation (
10) to obtain
using
Thus,
We first claim that the inverse operator of
is
in the subspace
S of
, given by
Clearly,
Letting
we have, for any
,
which implies that
is well-defined.
In addition,
is an inverse operator since
In fact,
and
is unique.
From Equation (
11), we find a series solution to Equation (
10) in
as
where
Clearly, the solution
given above is convergent in the space
. Indeed,
In particular, for
, we have
Evidently, if
, then Equation (
10) is
Example 3. The equation for :has a series solutionin . Remark 2. There are many investigations on numerical solutions to various time-fractional convection equations; see [14], for example. They are different from our inverse operator techniques and only find approximate solutions on finite domains in general, with or without convergence analysis. Solutions derived here are exact and well-defined in the space . However, it seems difficult and challenging to consider boundary value problems. In particular, if all , thenclearly is the solution satisfying the initial condition. In addition, the inverse operator method can be broadly applied to the study of various fractional partial differential equations, such as the generalized multi-term time-fractional diffusion-wave and partial integro-differential equation [4], the fractional convection–diffusion equation, and the generalized wave equation [15]. Recently, Li and Wang [14] applied the non-uniform L1/discontinuous Galerkin (DG) finite element method to study numerical solutions for the following two-dimensional problem for :