1. Introduction
Fractional differential equations (FDEs) arise from engineering and scientific disciplines regarding mathematical modeling of systems in the fields of physics, aerodynamics, chemistry, electrodynamics, and so on, involving derivatives of fractional order [
1,
2,
3,
4], where the theory of impulsive differential equations (IDEs) is particularly important for its wide spectrum of applications [
5,
6,
7]. The main reason for its applicability is due to the fact that impulsive differential problems appropriately describe many processes where, at certain moments, the states rapidly change, and these processes cannot be well modeled by classical differential equations [
8,
9]. Moreover, impulsive fractional differential equations (IFDEs) have found many promising applications [
10,
11].
Contrarily to the classical derivative, the fractional derivative is nonlocal, which leads to obstacles in studying IFDEs [
12,
13]. Recently, a new approach to modelling impulsive effects has been suggested and studied [
14]. This approach can be used when impulses in time are non-instantaneous; that is, impulses last over certain time intervals. The present paper does not deal with this new and interesting topic of non-instantaneous IDEs; rather, it focuses on yet another way to introduce impulses into differential equations.
Now, consider a continuous mapping , where and is an increasing sequence so that , and .
The objective here is to solve the following ODE:
with impulses
A conventional approach is to start with initial value
at
to solve (
1) for
and apply the impulse (
2) to obtain
, and then, we use this as the initial value to solve (
1) on
, and so on. During this iteration process, one can use any numerical method to solve the problem on each interval
,
.
It follows from (
1) that
for
, which leads to
for
.
This approach cannot be extended to FDEs, however, keeping the lower limit at
. Note that
for
, is a solution to the IFDE, as presented in [
13]:
for
, with (
2) and
, fixing the lower limit at
, where
is a generalized Caputo fractional derivative with lower limit at
.
Next, if the FDE version of (
1) is considered in the following form:
where
, then (
3) becomes
for
. Thus, one can study this type of IFDE (
6) with (
2) when the lower limits are changing at all impulses. Consequently,
is a generalized Caputo fractional derivative with lower limit at
. Similarly, it follows from (
7) that
for
. Because
, there is a memory effect in (
6), meaning that
where it is important to note that the integral kernels of the first term on the left-hand side are
but not
and that
holds only for
. Thus, (
8) shows that the memory effect of (
5) is not a sum of the memory effects of (
6) on each of these subintervals.
A comparative numerical study using examples of the above two IFDEs, with fixed lower limit (
5)–(
2) and with changing lower limit (
6), can be found in [
15].
One can study two types of IFDEs: the first is (
5)–(
2) with a solution formula (
4); the second is (
6)–(
2) with a solution formula (
7). One can see that gluing (
7) from 1 to
k together does not give a solution formula (
4). This is an essential difference between integer-order and fractional-order differential equations. This also implies that IFDE has no nonconstant periodic solutions when the lower limit is fixed at
[
16]. However, (
6)–(
2) may have periodic solutions when the impulses are periodic. As a matter of fact, periodic IFDEs create discrete dynamical systems, to which a general theory of difference equations can be applied [
17,
18].
The rest of this paper is organized as follows: Periodic IFDEs are discussed in
Section 2, while other possibilities of impulsive effects on FDEs are discussed in
Section 3 and
Section 4, inspired by [
19], wherein impulsive effects were not on the initial values but on the right-hand sides of FDEs. Finally, our conclusions and a discussion are presented in the last section.
2. Periodic IFDEs
Let
and consider
where
. Assume that
- (i)
is continuous and T-periodic in t;
- (ii)
there is a constant , such that for all and ;
- (iii)
is increasing, and , such that there is an with , and , for all .
As covered in [
2], under assumptions (i) and (ii), (
9) has a unique solution on
.
Now, consider the Poincaré mapping
Clearly, the fixed points of
P determine the
T-periodic solutions of (
9) ([
20], Lemma 2.2). The following existence and uniqueness result follows ([
21], Lemma 2.1 and Theorem 2.2).
Theorem 1. Under assumptions (i) and (ii), it holds thatwithwhere , and is the Mittag–Leffler function (see ([2], p. 40)). If (iii) holds as well and , then (9) has a unique T-periodic solution , which is asymptotically stable, namelyfor all and . To this end, the following existence can be established.
Theorem 2. Suppose that assumptions (i) and (iii) hold, and moreover,
- (iv)
there are constants and , such that for all and .
If in (10), then (9) has a T-periodic solution , satisfying Proof. On each interval
,
, Equation (
9) is equivalent to
Applying the Gronwall fractional inequality ([
3], Theorem 1) to (
12) leads to
which gives
for
. Consequently,
If
, then (
11) implies
. Hence,
P has a fixed point in the ball
by the Brouwer fixed point theorem. The proof is complete. □
Remark 1. Clearly, , but . Hence, (iv) does not guarantee the uniqueness of solutions.
From the above discussion, it follows that
has no periodic solutions. So, it suffices to consider only the periodic condition
More related results can be found in [
21].
Example 1. Consider the simplest case of a linear FDE with a period-one impulse sequence, described bywhere and A is an matrix, with A fixed point of (14) is determined bywhich is uniquely solvable, andif and only if . If , then the Lyapunov–Schmidt method [22] can be applied. Specifically, for the case of and with a vector product × and , where , one has Setting , where , and identifying with , i.e., , one obtains Then, (15) is transformed tofor . Thus, (14) becomes Since is a complex number, the only fixed point of (18) iswhich exists only if . Note that, for the matrix A defined in (16), . Now, consider a small perturbation to (17), yielding Then, in (19) expandingyieldsand Thus, (20) and (21) together givefor . Consequently, (14) becomes A fixed point of (22) is given by Solving the first equation of (23) gives It follows from the second equation of (23) with (24) that Finally, inserting (27) into (24) leads to In summary, the following result is obtained.
Theorem 3. Assuming (26), for any small , IFDE (19) has a fixed point given by (27) and (28). To this end, one can take specific values of q, η, ε, and in Theorem 3 to numerically study the dynamics of (18), which will not be further discussed here. 4. More General FDEs with Impulsive Effects
Consider another situation where the impulsive effects are not on the initial values but on the right-hand sides of the FDEs.
Let
and take an increasing sequence
with
and
. Consider
where
is an induced floor function given by
Thus, (
30) can be rewritten as
Consequently, (
30) has “impulses” at the nonlinearity but not at the argument
t. This is a kind of impulsive delay differential equation. The solution of (
30) is given by
Now, add control parameters
,
and modify (
30) to obtain the following:
Thus, (
32) becomes
which gives
A simple form of (
32) is
where the unperturbed part is given by
One may consider controlling the solutions of (
35) with (
34), which can be written as
Furthermore, one may consider a weighted control problem:
namely,
for
.
Finally, one may consider a more general form of (
30), such as
and extend the ideas described above, from (
30) to (
37).
Remark 2. If , i.e., with , then for the standard floor function . This kind of equation is studied in [19] for a scalar case and for integer-order derivatives. The simplest case of (
30) is its linear version
with
matrices
and
. The homogeneous case
defines a linear problem. This means that (
39) has a fundamental matrix solution
that solves
Therefore, the solution of (
39) is
,
. A semilinear case is
with
.
Example 3. Consider and a scalar case of (41): By (31), one hasfor . Note that (43) implies thatwhich gives a recurrent formula for computing the in (43). One may perform a numerical simulation of (42) for certain values of , which will not be further discussed here. The influence of the impulsive delay in (42) can be studied by introducing its weight dependence, which is as follows:where and is the fractional part of t. Thus, (43) becomes Consequently, the larger the η, the more is concentrated near j.
Example 4. Motivated by the above example, but with non-fixed lower limits in Caputo derivatives, consider This giveswhere and are Mittag–Leffler functions, which implies that The dynamics of are presented by a function When , (46) is a linear map, and it is stable for When , (46) is the well-known logistic map [17,23] with complex dynamics. The equationcharacterizes a border between simple and non-simple dynamics—the period-doubling bifurcation—as shown by Figure 1. Note that the equationcharacterizes a border between non-simple and chaotic dynamics. A period-three cycle emerges, and system (45) is chaotic in the sense of Li–Yorke chaos for every , as shown by Figure 1. 5. Conclusions and Discussion
Ordinary differential equations (ODEs) play a crucial role in modelling evolutional processes with orbits depending continuously on time. When orbits have discontinuities in time for certain values, ODEs with impulses are used, forming the impulsive ODEs (IODEs). Another extension of ODEs is to generalize their integer derivatives to noninteger ones, which leads to fractional calculus and fractional differential equations (FDEs), which have been well developed [
2,
5,
6,
8,
9]. The next natural development is the combination of the theories of IODEs and FDEs to create a new research direction of impulsive FDEs (IFDEs) [
13]. This paper proposes some new forms of modelling impulsive effects in FDEs. Usually, impulses are presented in the time evolution of solutions. Here, impulsive effects are not imposed on initial values but on the right-hand sides of FDEs. The proposed impulsive models differ from the common discontinuous and nonsmooth dynamical systems in many aspects, as discussed in [
24,
25]. Clearly, a combination of different impulses can be an interesting topic to study. Hopefully, the ideas presented here could contribute to the further development of impulsive evolution equations. Note that other types of impulsive models exist. This is another good topic for future research. For example, changing the lower limit at
instead of
opens up the opportunity to use this kind of IFDE in various applications (see, e.g., [
15]).