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R E S E A R C H

Open Access

Analytical solutions of linear

inhomogeneous fractional differential

equation with continuous variable

coefficients

Sunae Pak

1

, Huichol Choi

1

, Kinam Sin

1*

and Kwang Ri

2

*Correspondence:

18348668513@163.com

1Faculty of Mathematics, Kim Il Sung

University, Pyongyang, Democratic People’s Republic of Korea Full list of author information is available at the end of the article

Abstract

This paper proposes a series-representations for the solution of initial value problems of linear inhomogeneous fractional differential equation with continuous variable coefficients. It is proved that the solution of the problem is determined by adding the solution of the inhomogeneous differential equations with the homogeneous initial conditions to the linear combination of the canonical fundamental system of solution for corresponding homogeneous fractional differential equation and the

inhomogeneous initial values. The effectiveness of the theoretical analysis is illustrated with two examples.

Keywords: Linear inhomogeneous equation; Fractional differential equation; Continuous variable coefficient

1 Introduction

The fractional modelings have aroused much attention in the fields of both engineering and mathematics due to their significant applications in diverse scientific areas such as electromagnetism [1], behaviors of physical phenomena [2], signal processing [3], and control engineering [4]. A lot of theoretical research has been carried on the existence and uniqueness of solution of fractional differential equations (FDEs) over the last years [5–10]. Currently, methods for solving FDEs with initial conditions can be classified into two classes, namely, approximative method and analytical methods. Typical approxima-tive methods include the operational matrix method based on orthogonal functions, the predictor–corrector method, fractional Euler method, and so on ([11–16]). The most practical analytical methods are the Adomian decomposition method, the homotopy anal-ysis method, the homotopy perturbation method, the Laplace transform method, and the variational iteration method ([17–21]).

In [22], a solution of general linear inhomogeneous fractional differential equations with constant coefficients has been obtained by using the Adomian decomposition method and one proved that this solution is equal to the solution represented by Green’s func-tion. A theory on the system of linear inhomogeneous fractional differential equation has been studied, and the solution was represented in terms of the Green function for the case

(2)

of constant matrix coefficients in [23]. In [24], a power series solution method for some linear fractional differential equations with continuous variable coefficients has been pre-sented. In [25], a generalization of Duhamel’s method for one-term fractional differen-tial equations with constant coefficients has been proposed in the case when the classical Duhamel’s principle does not hold true for differential equations with Caputo fractional derivative. A fractional power series method has been introduced for the solution of frac-tional heat-like equations with variable coefficients in [26].

Our work proposes series-representations for the solution of linear inhomogeneous fractional differential equation with continuous variable coefficients and inhomogeneous initial conditions. The fractional derivative is of Caputo type in the proposed prob-lem.

The remainder of the paper is organized as follows. In Sect.2, some definitions of frac-tional calculus are introduced. Section3gives series-representations of solutions for initial value problems of linear inhomogeneous fractional differential equation with continuous variable coefficients. In Sect.4, the effectiveness of the proposed theory is illustrated with two examples. Finally, the conclusion to our work is summarized in Sect.5.

2 Preliminaries

Definition 2.1 Let R = (–∞, +∞) and R+= (0, +∞). We denote the space of functionsf byCn

r[0,T], wheref satisfiesf : (0,T]→R(∀T> 0) andtrf(n)(t)∈C[0,T] for 0≤r< 1. In particular, denoteC0

r[0,T] byCr[0,T].

Definition 2.2([27]) LetαR+,fCr[0,T], 0≤r< 1. Then

I0+αf(t) = 1

Γ(α)

t

0

(tτ)α–1f(τ), t> 0,

is called a fractional integral of orderα(α> 0) of the functionf in the sense of Riemann– Liouville. In particular, we denoteI0f(t) =f(t).

Definition 2.3([27]) Letn– 1 <αn,nN,InαfCn

γ[0,T] and 0≤γ < 1. Then

0+f(t) =DnInαf(t), Dn= d n

dtn,

is called the fractional derivative of orderα of the functionf in the sense of Riemann– Liouville.

Definition 2.4([27]) Letn– 1 <αn,nN,InαfCn

r[0,T], 0≤r< 1. Then

cDα

0+f(t) =D α 0+

f(t) – n–1

k=0

f(k)(0)

k! t k

,

is called the Caputo fractional derivative of orderαof the functionf.

Remark Whenα=n, we havecDα

(3)

Definition 2.5 LetnN. We define the set

ACn[a,b] :=

f : [a,b]→RDn–1fAC[a,b],D= d

dt

.

HereAC1[a,b] =AC[a,b] is the set of absolutely continuous functions on [a,b].

Definition 2.6 We denote by(L

1) the set of functionsf which are represented as an integral of orderα> 0 of some integrable functionϕL1(0,T), that is,f =Iαϕ.

3 Main result

Now we consider a linear inhomogeneous fractional differential equation with continuous variable coefficients

cDα0 0+y(t) +

m

i=1

ai(t)cDαi

0+y(t) =g(t), t∈[0,T], (1)

with the initial condition

Dky(t)|t=+0=bkR, k= 0, 1, . . . ,n0– 1, (2)

where α0,αiR+, i= 1, . . . ,msatisfyα0> 0,α0>α1>· · ·>αm≥0 andn0,ni are non-negative integers that satisfyn0– 1 <α0≤n0,ni– 1 <αini,i= 1, . . . ,m.

We can write the corresponding homogeneous differential equation of Eq. (1) by

cDα0 0+y(t) = –

m

i=1

ai(t)cDαi

0+y(t), 0 <t<T. (3)

In order to consider all possible cases for the homogeneous equation (3), we introduce the following index setsHjprovided byαi,i= 0, 1, . . . ,m:

Hj=d{i: 0≤αij,i= 1, . . . ,m}, j= 0, 1, . . . ,n0– 1.

Here, we sethj=minHjifHj=∅(where∅is the empty set).

Remark LetkHjαkjandHiHj(i<j). IfHj=∅, lethj=minHj which is the smallest index of fractional orders of Eq. (3) that do not exceedj. Then it is evident that

mhj+1 is the number of element ofHjandhihj(i<j). Thus wheni<j,hihjrepresents the number of such orderαkthati<αkjand in particular, ifhi=hj, then Eq. (3) has no such fractional ordersαkthati<αkj.

Then there are the following possible cases:

Case 1.H0=∅. In this caseHj=∅,j= 0, 1, . . . ,n0– 1.

Case 2.n0≥2 and there exists aj0∈ {0, 1, . . . ,n0– 2}such thatHj0=∅andHj0+1=∅. In this caseHj=∅,j= 0, 1, . . . ,j0andHj=∅,j=j0+ 1, . . . ,n0– 1.

(4)

Definition 3.1 The linear homogeneous fractional differential equation (3) is called of

type 1,2,3, respectively, when Eq. (3) correspond to the cases 1, 2, 3 dependent on the patterns of distances between adjacent fractional orders.

Definition 3.2 A system of functionsyj(t) (j= 0, 1, . . . ,n0– 1) is called acanonical

funda-mental systemof solutions of the homogeneous equation (3) if it satisfies

cDα0 0+yj(t) = –

m

i=1

ai(t)cDαi

0+yj(t), 0 <t<T,

Dkyj(t)|t=+0=

⎧ ⎨ ⎩

1, j=k,

0, j=k,k,j= 0, 1, . . . ,n0– 1.

First, we consider the problem for solving the linear inhomogeneous fractional differ-ential equations Eq. (1) with variable coefficients and the homogeneous initial condition

Dky(t)|t=0+= 0, k= 0, 1, . . . ,n0– 1. (4)

Lemma 3.1 Let g(t),ai(t)∈C[0,T],i= 1, . . . ,m.Then the initial value problem(1)and

(4)has the unique solution y(t)∈0,n0–1[0,T],which is the limit y(t) =lim

l→∞yl(t)of the

approximation sequence

y0(t) =0

0+g(t), (5)

yl(t) =y0(t) –I0+α0

m

i=1

ai(t)cDαi0+yl–1(t), l= 1, 2, . . . , (6)

where Cα0,n0–1[0,T] :=Cα0,n0–1

0 [0,T] ={y(x)∈Cn0–1[0,T],cD α0

0+yC[0,T]}and the norm

is

yCα0,n0–1[0,T]= n0–1

k=0

y(k)C[0,T]+cDα0 0+yC[0,T].

Proof First we prove the uniqueness and existence of solution for the initial value problem (1) and (4). Let assume thaty(t)∈0,n0–1[0,T] satisfy Eqs. (1) and (4). Then ifcDα0

0+y(t) =

z(t), we takecDα0

0+y(t)∈C[0,T] andz(t)∈C[0,T]. We can rewrite as

0 0+cD

α0 0+y(t) =I

α0 0+z(t).

Also the left of the above equation has been changed,

0 0+cD

α0

0+y(t) =y(t) – n0–1

j=0

Djy(0)Φj+1(t), Φj+1(t) =

tj

j!.

By the homogeneous initial condition (4), we obtain

(5)

Namelyy(t) =I0+α0z(t). ThereforecDαi 0+y(t) =I

α0αi

0+ z(t) and Eq. (1) changes to the integral equation

z(t) + m

i=1

ai(t)0–αi

0+ z(t) =g(t). (7)

Thus, for the solutiony(t)∈0,n0–1[0,T] of Eqs. (1) and (4),cDα0

0+y(t) =z(t) satisfies the integral equation Eq. (7).

Conversely let assume thatz(t)∈C[0,T] is the solution of Eq. (7). Sinceg(t)∈C[0,T],

I0+α0z(t) +I0+α0

m

i=1

ai(t)I0+α0αiz(t) =I0+α0g(t).

Lety(t) :=0

0+z(t). Then we havecD αi 0+y(t) =I

α0αi 0+ z(t) and

y(t) +I0+α0

m

i=1

ai(t)cDαi 0+y(t) =I

α0 0+g(t).

That is,

cDα0 0+y(t) +

m

i=1

ai(t)cDαi

0+y(t) =g(t).

Also we get

Dky(t)|t=+0=DkI0+α0z(t)|t=+0=I0+α0kz(t)|t=+0= 0, (k= 0, 1, . . . ,n0– 1).

Therefore for the solution z(t)∈C[0,T] of integral equation Eq. (7), 0

0+z(t) =y(t)∈

Cα0,n0–1[0,T] satisfies the initial value problem (1) and (4).

Thus the uniqueness and existence of solution for Eqs. (1) and (4) are equivalent to the ones of integral equation Eq. (7).

Now let prove the uniqueness and existence of solution for integral equation (7). Equa-tion (7) can be rewritten

z(t) =g(t) – m

i=1

ai(t)I0+α0αiz(t). (8)

We define the operatorT byTz(t) :=g(t) –mi=1ai(t)Iα0αi

0+ z(t). Then Eq. (8) is expressed

z(t) =Tz(t), namelyT:C[0,T]→C[0,T].

In C[0,T], we use thek-norm zk=maxkekt|z(t)|which is equivalent to the max-norm.

For∀t∈[0,T], by the fact that0–αiektekt

0–αi, the following expression is derived:

Tz1(t) –Tz2(t)

=

m

i=1

ai(t)Iα0αi 0+

z1(t) –z2(t)

m

i=1

aimaxI

α0αi

(6)

= m

i=1

aimaxI

α0αi

0+ ektektz1(t) –z2(t)≤ z1–z2k m

i=1

aimaxI

α0αi 0+ ekt

z1–z2k m

i=1

aimax

ekt

kα0αi.

So we can obtain

ektTz1(t) –Tz2(t)≤

m

i=1

aimax

1

0–αi

z1–z2k.

Ifw(k) :=mi=1aimaxkα0–1αi, then∃k0∈R+;∀k>k0,w(k0) < 1,w0:=w(k0),Tz1–Tz2k0

w0z1–z2k0, i.e. the operator T :C[0,T]→C[0,T] is a contractive operator which is relative to · k0. By the equivalence of · max and · k0,T :C[0,T]→C[0,T] is the contractive operator which is relative to · max.

Therefore by using Banach fixed point theorem, the integral equation (7) has a unique solution in the sense of the norm · maxand the sequence{zn(t)}which is constructed by

zn(t) =g(t) –im=1ai(t)Iα0αi

0+ zn–1(t) converges in the sense of the norm · maxinC[0,T].

Next let prove the convergence of the approximative sequence (5) and (6). Sinceg(t)∈

C[0,T], the sequence{zn(t)}constructed by the approximative expression

⎧ ⎨ ⎩

z0=g(t),

zn=g(t) –

m i=1ai(t)I

α0αi 0+ zn–1(t),

(9)

convergent in the sense of · max.

From Eq. (9),

⎧ ⎨ ⎩

I0+α0z0=I0+α0g(t),

0

0+zn=0+0g(t) –I α0 0+

m i=1ai(t)I

α0–αi 0+ zn–1(t)

and since0

0+zk=yk,I0+α0αizk–1(t) =cDα0+iyk(t), we have

⎧ ⎨ ⎩

y0=I0+α0g(t),

yl=y0Iα0 0+

m

i=1ai(t)cD αi 0+yl(t),

i.e., Eqs. (5) and (6), whereylCα0,n0–1[0,T].

We prove the convergence of sequence{yl}inCα0,n0–1[0,T]. Sinceyk=Iα0 0+zk,

cDα0 0+yk=zk,

Dlyk=I0+α0lzk, l= 0, 1, . . . ,n0– 1,

are obtained. So

cDα0

0+ykmax=zkmax,

DlykmaxT

α0–l

Γ(α0–l+ 1)

(7)

are satisfied. From the above two equations, we have

n0–1

l=1

Dlykmax+cDα0

0+ykmax≤

n0–1

l=1

0–l

Γ(α0–l+ 1) + 1

zkmax.

Since {zk} converges, the sequence {yk} constructed by Eqs. (5) and (6) converges in

0,n0–1[0,T].

Lemma 3.2 Letγ =n0–α0(∈[0, 1)),n0=n1, ai1[0,T]and D n0α0

0+ aiC[0,T],i= 1, . . . ,m.Also let assume that H0=∅,that is, Eq. (3)is of type1.Then there exists the

unique canonical fundamental system yj(t)∈Cn0

γ [0,T], (j= 0, 1, . . . ,n0– 1)of the solution

for Eq. (3)and it is written

yj(t) =Φj+1(t) +

k=0

(–1)k+10 0+

m

i=1

ai(t)I α0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j= 0, 1, . . . ,n0– 1, (10)

where

Φj+1(t) =

tj

j!.

Proof Let find the canonical system as the limit inCn0

γ [0,T] of the approximation sequence

y0j(t) =Φj+1(t), (11)

ylj+1(t) =Φj+1(t) –I α0 0+

m

i=1

ai(t)cD αi 0+ylj(t)

, l= 0, 1, 2, . . . . (12)

First, we will obtainy0(t). Letj= 0 in Eq. (11), theny00(t) =Φ1(t) and from Eq. (12), we have

y10(t) =Φ1(t) –I α0 0+

m

i=1

ai(t)cD αi

0+y00(t) =Φ1(t) –I0+α m

i=1

ai(t)cD αi

0+Φ1(t). (13)

Also

cDαi

0+Φ1(t) =D αi 0+

Φ1(t) – ni–1

k=0

DkΦ1(0)Φk+1(t)

, i= 1, 2, . . . ,m. (14)

SinceH0=∅, we haveh0=minH0=m. Fori=m,αm=nm= 0,

cDαi

0+Φ1(t) =Dαm0+Φ1(t) =Φ1(t).

Ifi= 1, . . . ,m– 1, thenαi> 0 and fromni– 1 <αini, we haveni≥1. Since

DkΦ1(0) =

⎧ ⎨ ⎩

1, k= 0,

(8)

in (14), thencDαi

0+Φ1(t) = 0 fori= 1, . . . ,m– 1 and

cDαi 0+Φ1(t) =

⎧ ⎨ ⎩

Φ1(t), i=h0=m,

0, i= 1, . . . ,m– 1.

Substituting this into Eq. (13), then the first approximation ofy0(t) is given by

y10(t) =Φ1(t) –I α0

0+am(t)Φ1(t) (15)

and sinceh0=mandαm= 0, we can rewrite it as

y10(t) =Φ1(t) –I0+α0 m

i=h0

ai(t)Φ1–αi(t).

Thus we get the first term (k= 0) of Eq. (10) in the case ofj= 0. Now let provey10(t)∈Cn0

γ [0,T]. From Eq. (15), we have

Dn0–1y10(t) =Dn0–1Φ1(t) –Dn0–1I0+α0am(t)Φ1(t) = –I0+α0n0+1am(t)Φ1(t).

Fromam(t)Φ1(t) =am(t)∈C[0,T] andα0–n0+1 > 0,I0+α0n0+1am(t)Φ1(t)∈C[0,T] is found, that is,

y10(t)∈Cn0–1[0,T].

On the other hand, from am(t)Φ1(t) =am(t)∈1[0,T] andα0–n0+ 1 > 0, we have

0–n0+1

0+ am(t)Φ1(t)∈1[0,T]. Therefore

Dn0y10(t) =Dn0Φ1(t) –Dn0I0+α0am(t)Φ1(t) = –DI0+α0–n0+1am(t)Φ1(t)∈[0,T].

Thus we provedy1

0(t)∈Cγn0[0,T].

Next we consider the case ofj= 0,l= 1 in Eq. (12) to find the second approximation of

y0(t). We have

y20(t) =Φ1(t) –I α0 0+

m

i=1

ai(t)cD αi 0+y10(t)

=Φ1(t) –I0+α0 m

i=1

ai(t)cDαi 0+

Φ1(t) –I0+α0 m

i=h0

ai(t)Φ1–αi(t)

=Φ1(t) –I α0 0+

m

i=1

ai(t)cD αi

0+Φ1(t) +I α0 0+

m

i=1

ai(t)cD αi 0+I

α0 0+

m

i=h0

ai(t)Φ1–αi(t).

Now letf(t) :=mi=h0ai(t)Φ1–αi(t) and calculatecD αi 0+I

α0

0+f(t). Then we get

cDαi 0+I

α0 0+f(t) =D

αi 0+

I0+α0f(t) – ni–1

k=0

DkI0+α0f(t)

t=+0

(9)

Here sincekni– 1 <αi<α0,i= 1, . . . ,m, we haveα0–k> 0,k= 0, 1, . . . ,ni– 1 and thus we can rewrite it as

DkIα0

Thus the second approximation is given as

y20(t) =Φ1(t) –I0+α0

Now under the assumption that thelth approximation ofy0(t) is provided by

(10)

=Φ1(t) –I0+α0 elementy0(t) of the canonical system

(11)

Ifihj, 0αijandnij. ThusDkΦj+1(0) = 0,k= 0, . . . ,n0– 1. That is, we get

Therefore the first approximation ofyj(t) is provided by

y1j(t) =Φj+1(t) –I

The second approximation ofyj(t) is given by

y2j(t) =Φj+1(t) –I0+α0

By induction, thenth approximation ofyj(t) is given by

(12)

Therefore

yj(t) = lim n→∞y

n

j(t) =Φj+1(t) +

k=0

(–1)k+1I0+α0

m

i=1

ai(t)0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t).

Lemma 3.3 Let us assume that n0>n1,aiC[0,T] (i= 1, . . . ,m)andH0=∅.Then there

exists the unique canonical fundamental system

yj(t)∈0,n0–1[0,T], j= 0, 1, . . . ,n 0– 1,

of solutions for Eq. (3)and it is written by

yj(t) =Φj+1(t) +

k=0

(–1)k+10 0+

m

i=1

ai(t)I α0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j= 0, 1, . . . ,n1– 1, (16)

yj(t) =Φj+1(t) +

k=0

(–1)k+1I0+α0

m

i=1

ai(t)I0+α0αi

k m

i=1

ai(t)Φj+1–αi(t),

j=n1,n1+ 1, . . . ,n0– 1. (17)

Proof Let find the canonical system as the limit of the approximation sequence (11) and (12). Fixingj= 0, 1, . . . ,n0– 1, we find thejth elementyj(t) of the canonical system.

y0j(t) =Φj+1(t),

y1j(t) =Φj+1(t) –I0+α0 m

i=1

ai(t)cDαi

0y0j(t) =Φj+1(t) –I0+α0 m

i=1

ai(t)cDαi 0Φj+1(t).

Let us note that, fork= 0, 1, . . . ,ni– 1,

DkΦj+1(0) =

⎧ ⎨ ⎩

1, k=j,

0, k=j.

Sincen0>n1≥ni, forj= 0, 1, . . . ,n1– 1, we get

cDαi

0+Φj+1(t) =

⎧ ⎨ ⎩

Dαi

0+Φj+1(t), hjim,

0, 1≤i<hj. (18)

Ifj=n1, . . . ,n0– 1, thenk<jand thus we get

cDαi

(13)

Therefore the first approximation ofyj(t) is given by can rewrite (20) as

y2j(t) =Φj+1(t) –I0+α0

Thus we have the representation of the second approximation ofyj(t) as

(14)

Forn= 3, 4, . . . , we can findynj(t) by induction and, by lettingn→ ∞, we get the represen-tation (16) and (17) of the canonical fundamental system.

Lemma 3.4 Let0 <γ =n0–α0< 1, n0=n1, ai1[0,T]and D n0α0

0+ aiC[0,T], i= 1, . . . ,m.Let assume that Eq. (3)is of type2.That is,let assume that n0≥2 and there

exists a j0∈ {0, 1, . . . ,n0– 2}such thatHj0=∅andHj0+1=∅.Then there exists the unique

canonical fundamental system yj(t)∈Cγn0[0,T],j= 0, 1, . . . ,n0– 1of solutions for Eq. (3)

and it is written by

yj(t) =Φj+1(t), j= 0, 1, . . . ,j0, (21)

yj(t) =Φj+1(t) +

k=0

(–1)k+1I0+α0

m

i=1

ai(t)0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j=j0+ 1, . . . ,n0– 1. (22)

Proof Similarly, we can see that the first approximation ofyj(t) is written

y1j(t) =Φj+1(t), j= 0, 1, . . . ,j0,

y1j(t) =Φj+1(t) –I0+α0 m

i=hj

ai(t)Φj+1–αi(t), j=j0+ 1, . . . ,n0– 1.

We gety1

j(t)∈Cγn0[0,T],j=j0+ 1, . . . ,n0– 1. Also the second approximation ofyj(t) is given as

y2j(t) =Φj+1(t), j= 0, 1, . . . ,j0,

y2j(t) =Φj+1(t) + 1

k=0

(–1)k+10 0+

m

i=1

ai(t)I α0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j=j0+ 1, . . . ,n0– 1.

By induction, we get thenth approximation ofyj(t),

ynj(t) =Φj+1(t), j= 0, 1, . . . ,j0,

ynj(t) =Φj+1(t) + n–1

k=0

(–1)k+10 0+

m

i=1

ai(t)I α0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j=j0+ 1, . . . ,n0– 1.

That is, the canonical fundamental system of solutions for Eq. (3) is given by (21) and (22) and we getyj(t)∈Cγn0[0,T],j= 0, 1, . . . ,n0– 1.

Lemma 3.5 Lets assume that n0>n1and ai∈[0,T],i= 1, . . . ,m.Lets assume that Eq. (3)

(15)

Hj0=∅andHj0+1=∅.Then there exists the unique canonical fundamental system yj(t)∈

0,n0–1[0,T],j= 0, 1, . . . ,n

0– 1of solution for Eq. (3)and it is written by

yj(t) =Φj+1(t), j= 0, 1, . . . ,j0, (23)

yj(t) =Φj+1(t) +

k=0

(–1)k+1I0+α0

m

i=1

ai(t)0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j=j0+ 1, . . . ,n1– 1, (24)

yj(t) =Φj+1(t) +

k=0

(–1)k+10 0+

m

i=1

ai(t)Iα0αi 0+

k m

i=1

ai(t)Φj+1–αi(t),

j=n1,n1+ 1, . . . ,n0– 1. (25)

Proof Similarly, we can see the first approximation ofyj(t) is given by

y1j(t) =Φj+1(t), j= 0, 1, . . . ,j0,

y1j(t) =Φj+1(t) –I0+α0 m

i=hj

ai(t)Φj+1–αi(t), j=j0+ 1, . . . ,n1– 1,

y1j(t) =Φj+1(t) –I0+α0 m

i=1

ai(t)Φj+1–αi(t), j=n1, . . . ,n0– 1.

Also we get the second approximation ofy1 j(t),

y2j(t) =Φj+1(t), j= 0, 1, . . . ,j0,

y2j(t) =Φj+1(t) + 1

k=0

(–1)k+10 0+

m

i=1

ai(t)I α0–αi 0+

k m

i=hj

ai(t)Φj+1–αi(t),

j=j0+ 1, . . . ,n1– 1,

y2j(t) =Φj+1(t) + 1

k=0

(–1)k+1I0+α0

m

i=1

ai(t)I0+α0αi

k m

i=1

ai(t)Φj+1–αi(t),

j=n1,n1+ 1, . . . ,n0– 1.

In a similar way to the above proof, we can get thenth approximation ofyj(t) and then, takingn→ ∞, we can get the canonical fundamental system (23) and (24) and (25) and

yj(t)∈0,n0–1[0,T],j= 0, 1, . . . ,n

0– 1.

Lemma 3.6 Let0 <γ =n0–α0< 1and assume that ai1[0,T],i= 1, . . . ,m.Let us

assume that Eq. (3)is of type3.That is,let assume thatHn0–1=∅.Then Eq. (3)has the

unique canonical fundamental system{yj(t) :j= 0, 1, . . . ,n0– 1}of solutions in Cn0γ [0,T]

and it is represented as

(16)

Proof Lety0j(t) =Φj+1(t),j= 0, 1, . . . ,n0– 1 and calculate the first approximation ofyj(t). Then we have

y1j(t) =Φj+1(t) –I0+α0 m

i=1

ai(t)cDαi 0+Φj+1(t).

From the assumption ofHn0–1={i: 0≤αin0– 1,i= 1, . . . ,m}=∅, it is evident that

n0– 1 <αin0for alli= 1, . . . ,mand thus

cDαi

0+Φj+1(t) =Dαi0+

Φj+1(t) – n0–1

k=0

DkΦj+1(0)Φk+1(t)

= 0, j= 1, . . . ,n0– 1,

andy1

j(t) =Φj+1(t),j= 1, . . . ,n0– 1. Similarly, we can easily find

ynj(t) =Φj+1(t), j= 0, . . . ,n0– 1,

and thus we can get

yj(t) =Φj+1(t)∈Cn0γ [0,T], j= 0, . . . ,n0– 1.

Theorem 3.1 Let g(t),ai(t)∈C[0,T],i= 1, . . . ,m.Then there exists the unique solution

y(t)∈Cα0,n0–1[0,T]of the initial value problem(1)and(4)and it is represented by

y(t) =

k=0 (–1)kIα0

0+

m

i=1

ai(t)I α0–αi 0+

k

g(t). (27)

Proof From the assumptions and Lemma3.1follow the existence and uniqueness of the solution of Eqs. (1) and (4). Now we have to find this solution.

From Lemma3.1, the first approximation solution is given by

y1(t) =I0+α0g(t) –I0+α0

m

i=1

ai(t)cDαi0+I0+α0g(t).

With a view on the definition of the Caputo fractional derivative and the integrability of

I0+α0αig(t), we have

cDαi 0+I

α0 0+g(t) =D

αi 0+

I0+α0g(t) – ni–1

j=1

DjI0+α0g(0)Φj+1(t)

=Dαi0+I0+α0g(t)

=Dαi 0+I

αi 0+I

α0–αi 0+ g(t) =I

α0–αi 0+ g(t).

So, the first approximation solution can be rewritten

y1(t) =0 0+g(t) –I

α0 0+

m

i=1

ai(t)0–αi 0+ g(t) =I

α0 0+g(t) –I

α0 0+

m

i=1

ai(t)0–αi 0+

g(t)

= 1

k=0 (–1)kI0+α0

m

i=1

ai(t)0–αi 0+

k

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Dn0–1y1(t) =I0+α0n0+1g(t) –I0+α0n0+1

Next, we find the second approximation solution, i.e.,l= 2 in the expression of Eq. (6):

y2(t) =0

Thus, we get the second approximation solution

y2(t) =

Now, we inductively find the (l+ 1)th approximation solution when thelth approximation solution for anylNis provided by

(18)

Then we have

Therefore, we see that, for any natural numbern, thenth approximation solution is

yn(t) =

that the case1holds.Then the initial value problem(1)and(2)has the unique solution y(t)∈Cα0,n0–1[0,T]Cn0

where yj(t)is the canonical fundamental system of solution to the corresponding homoge-neous equation

which is obtained from Lemma3.2.

Proof The proof follows from Theorem3.1and the linearity of the initial value problem (1) and (2).

Corollary 3.2.1 Let n0– 1 <α0<n0,n0>n1,g(t)∈C[0,T]and aiC[0,T],i= 1, . . .m.

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solution y(t)∈0,n0–1[0,T]and it is represented as

y(t) = n0–1

j=0

bjyj(t) +

k=0 (–1)kIα0

0+

m

i=1

ai(t)I α0–αi 0+

k

g(t),

where yj(t)is obtained from Lemma3.3.

Corollary 3.2.2 Let n0– 1 <α0≤n0and n0=n1.Assume that aiCr1[0,T],D n0α0 0+ ai

C[0,T],i= 1, . . . ,m for anyγ such that0 <γ =n0–α0< 1and g(t)∈C[0,T].Moreover,

assume that the case2holds true.Then the initial value problem(1)and(2)has the unique solution y(t)∈Cα0,n0–1[0,T]Cn0

γ [0,T]and it is represented as

y(t) = n0–1

j=0

bjyj(t) +

k=0 (–1)kI0+α0

m

i=1

ai(t)0–αi 0+

k

g(t),

where yj(t)is obtained from Lemma3.4.

Corollary 3.2.3 Let n0– 1 <α0<n0,n0>n1,g(t)∈C[0,T]and aiC[0,T],i= 1, . . . ,m.

Assume that the case2holds true.Then the initial value problem(1)and(2)has the unique solution y(t)∈0,n0–1[0,T]and it is represented as

y(t) = n0–1

j=0

bjyj(t) +

k=0 (–1)kIα0

0+

m

i=1

ai(t)I α0–αi 0+

k

g(t),

where yj(t)is obtained from Lemma3.5.

Corollary 3.2.4 Let aiCr1[0,T],i= 1, . . . ,m for r such that0 <γ <α0–n0+ 1.Moreover,

assume that the case3holds true.Then the initial value problem(1)and(2)has the unique solution y(t)∈Cα0,n0–1[0,T]Cn0

γ [0,T]and it is represented as

y(t) = n0–1

j=0

bjyj(t) +

k=0 (–1)kI0+α0

m

i=1

ai(t)0–αi 0+

k

g(t),

where yj(t)is obtained from Lemma3.6.

4 Examples

Example1 We consider the fractional differential equation with continuous variable co-efficients as

⎧ ⎨ ⎩

cD0.8

0+y(t) +ts·cD0.30+y(t) =,

y(t)|t=+0= 0.

(29)

Then we see that Eq. (29) satisfy the conditions of Theorem3.1. We have

y(t) =

k=0

(–1)kI0+0.8tksI0+0.5ktβ=I0+0.8+

k=1

(20)

=I0+0.8– 1

Thai is, the solution of Example1is expressed as

y(t) = Γ(β+ 1)

Example2 We discuss the linear inhomogeneous fractional differential equation with continuous variable coefficients as

are satisfied, we have

(21)

Figure 1The error between the exact solution and series-representation solution

Therefore the solution expressiony(x) of the proposed problem is obtained as the above equation. The error between the exact solution and series-representation solution is

y= Γ(1.5) 2Γ(2.2)t

3 2

Γ(1.5)

t

0

(tz)0.5z1.5E0.7,2.2(–z)dz

– 3

Γ(2.2)

t

0

(tz)0.5z2.5E0.7,3.2(–z)dz.

We can know that the error value is equal to almost zero. The error graph is shown in Fig.1.

5 Conclusion

In this paper, we have obtained series-representations for the solution of initial value prob-lems of linear inhomogeneous fractional differential equations with continuous variable coefficients and inhomogeneous initial conditions. We have proved that the solution of the problem is determined by adding the solution of the inhomogeneous differential equations with the homogeneous initial conditions to the linear combination of the canonical fun-damental system of solution for the corresponding homogeneous fractional differential equation and the inhomogeneous initial values. The effectiveness of the proposed the-ory is illustrated with two examples. The representation of the solution for a multi-term fractional differential equation under general conditions will be the object of our future research.

Acknowledgements

The authors thank the referee for careful reading and helpful suggestions on the improvement of the manuscript.

Funding Not applicable.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All authors carried out the proof and conceived of the study. All authors read and approved the final manuscript.

Author details

1Faculty of Mathematics, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea.2Department of

Applied Mathematics, Kim Chaek University of Technology, Pyongyang, Democratic People’s Republic of Korea.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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References

1. Engheta, N.: On fractional calculus and fractional multipoles in electromagnetism. IEEE Trans. Antennas Propag.44, 554–566 (1996)

2. Ahmadian, A., Salahshour, S., Seng Chan, C.: Fractional differential systems: a fuzzy solution based on operational matrix of shifted Chebyshev polynomials and its applications. IEEE Trans. Fuzzy Syst.25(1), 218–236 (2016) 3. Ortigueira, M.D., Machado, J.A.T.: Fractional signal processing and applications. Signal Process.83, 2285–2286 (2003) 4. Dehghan, M., Hamedi, E.A., Khosravian-Arab, H.: A numerical scheme for the solution of a class of fractional variational

and optimal control problems using the modified Jacobi polynomials. J. Vib. Control22(6), 1547–1559 (2016) 5. Bai, Z., Sun, S., Chen, Y., Bai, Z., Sun, S., Chen, Y.: The existence and uniqueness of a class of fractional differential

equations. Abstr. Appl. Anal.2014, Article ID 486040 (2014)

6. Lv, L., Wang, J., Wei, W.: Existence and uniqueness results for fractional differential equations with boundary value conditions. Opusc. Math.31, 629–643 (2011)

7. Mahto, L., Abbas, S.: Existence and uniqueness of solution of Caputo fractional differential equations. AIP Conf. Proc.

1479, 896–899 (2012)

8. Tariboon, J., Sitthiwirattham, T., Ntouyas, S.K.: Boundary value problems for a new class of three-point nonlocal Riemann–Liouville integral boundary conditions. Adv. Differ. Equ.2013, 213 (2013)

9. Liu, S.L., Li, H.L., Dai, Q., Liu, J.P.: Existence and uniqueness results for nonlocal integral boundary value problems for fractional differential equations. Adv. Differ. Equ.2016, 122 (2016)

10. Badr, M., Yazdani, A., Jafari, H.: Stability of a finite volume element method for the time-fractional advection-diffusion equation. Numer. Methods Partial Differ. Equ.34(5), 1459–1471 (2018)

11. Doha, E.H., Bhrawy, A.H., Baleanu, D., Ezz-Eldien, S.S.: On shifted Jacobi spectral approximations for solving fractional differential equations. Appl. Math. Comput.219, 8042–8056 (2013)

12. Sin, K., Chen, M., Choi, H., Ri, K.: Fractional Jacobi operational matrix for solving fuzzy fractional differential equation. J. Intell. Fuzzy Syst.33, 1041–1052 (2017)

13. Diethelm, K., Ford, N.J., Freed, A.D.: A predictor corrector approach for the numerical solution of fractional differential equations. Nonlinear Dyn.29, 3–22 (2002)

14. Doha, E.H., Bhrawy, A.H., Ezz-Eldien, S.S.: A Chebyshev spectral method based on operational matrix for initial and boundary value problems of fractional order. Comput. Math. Appl.62, 2364–2373 (2011)

15. Mazandarani, M., Vahidian Kamyad, A.: Modified fractional Euler method for solving fuzzy fractional initial value problem. Commun. Nonlinear Sci. Numer. Simul.18, 12–21 (2013)

16. Sadeghi Roshan, S., Jafari, H., Baleanu, D.: Solving FDEs with Caputo–Fabrizio derivative by operational matrix based on Genocchi polynomials. Math. Methods Appl. Sci.41(18), 9134–9141 (2018)

17. Daftardar-Gejji, V., Jafari, H.: Adomian decomposition: a tool for solving a system of fractional differential equations. J. Math. Anal. Appl.301, 508–518 (2005)

18. Jafari, H.: Numerical solution of time-fractional Klein–Gordon equation by using the decomposition methods. J. Comput. Nonlinear Dyn.11(4), 041015 (2016)

19. Jafari, H., Momani, S.: Solving fractional diffusion and wave equations by modified homotopy perturbation method. Phys. Lett. A370, 388–396 (2007)

20. Das, S.: Analytical solution of a fractional diffusion equation by variational iteration method. Comput. Math. Appl.57, 483–487 (2009)

21. Firoozjaee, M.A., Jafari, H., Lia, A., Baleanu, D.: Numerical approach of Fokker–Planck equation with Caputo–Fabrizio fractional derivative using Ritz approximation. J. Comput. Appl. Math.339, 367–373 (2018)

22. Hu, Y., Luo, Y., Lua, Z.: Analytical solution of the linear fractional differential equation by Adomian decomposition method. J. Comput. Appl. Math.215, 220–229 (2008)

23. Bonilla, B., Rivero, M., Trujillo, J.J.: On system of linear fractional differential equation with constant coefficients. Appl. Math. Comput.181, 68–78 (2007)

24. Kilbas, A.A., Rivero, M., Rodríguez-Germá, L., Trujillo, J.J.:α-Analytic solutions of some linear fractional differential equations with variable coefficients. Appl. Math. Comput.187, 239–249 (2007)

25. Umarov, S.R., Saidamatov, E.M.: A generalization of Duhamel’s principle for differential equations of fractional order. Dokl. Math.75(1), 94–96 (2007)

26. Cui, R., Ban, T.: An analytical solution for a fractional heat-like equation with variable coefficients. Therm. Sci.21(4), 1759–1764 (2017)

Figure

Figure 1 The error between the exact solution and

References

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