
A study was conducted on the existence of solutions for a class of nonlinear Caputo type higher-order fractional Langevin equations with mixed boundary conditions on a star graph with k+1 nodes and k edges. By applying a variable transformation, a system of fractional differential equations with mixed boundary conditions and different domains was converted into an equivalent system with identical boundary conditions and domains. Subsequently, the existence and uniqueness of solutions were verified using Krasnoselskii's fixed point theorem and Banach's contraction principle. In addition, the stability results of different types of solutions for the system were further discussed. Finally, two examples are illustrated to reinforce the main study outcomes.
Citation: Gang Chen, Jinbo Ni, Xinyu Fu. Existence, and Ulam's types stability of higher-order fractional Langevin equations on a star graph[J]. AIMS Mathematics, 2024, 9(5): 11877-11909. doi: 10.3934/math.2024581
[1] | Mohamed A. Barakat, Abd-Allah Hyder, Doaa Rizk . New fractional results for Langevin equations through extensive fractional operators. AIMS Mathematics, 2023, 8(3): 6119-6135. doi: 10.3934/math.2023309 |
[2] | Abdelatif Boutiara, Mohammed S. Abdo, Manar A. Alqudah, Thabet Abdeljawad . On a class of Langevin equations in the frame of Caputo function-dependent-kernel fractional derivatives with antiperiodic boundary conditions. AIMS Mathematics, 2021, 6(6): 5518-5534. doi: 10.3934/math.2021327 |
[3] | Arjumand Seemab, Mujeeb ur Rehman, Jehad Alzabut, Yassine Adjabi, Mohammed S. Abdo . Langevin equation with nonlocal boundary conditions involving a ψ-Caputo fractional operators of different orders. AIMS Mathematics, 2021, 6(7): 6749-6780. doi: 10.3934/math.2021397 |
[4] | Xiaoming Wang, Rizwan Rizwan, Jung Rey Lee, Akbar Zada, Syed Omar Shah . Existence, uniqueness and Ulam's stabilities for a class of implicit impulsive Langevin equation with Hilfer fractional derivatives. AIMS Mathematics, 2021, 6(5): 4915-4929. doi: 10.3934/math.2021288 |
[5] | Weerawat Sudsutad, Chatthai Thaiprayoon, Sotiris K. Ntouyas . Existence and stability results for ψ-Hilfer fractional integro-differential equation with mixed nonlocal boundary conditions. AIMS Mathematics, 2021, 6(4): 4119-4141. doi: 10.3934/math.2021244 |
[6] | Rizwan Rizwan, Jung Rye Lee, Choonkil Park, Akbar Zada . Qualitative analysis of nonlinear impulse langevin equation with helfer fractional order derivatives. AIMS Mathematics, 2022, 7(4): 6204-6217. doi: 10.3934/math.2022345 |
[7] | Zheng Kou, Saeed Kosari . On a generalization of fractional Langevin equation with boundary conditions. AIMS Mathematics, 2022, 7(1): 1333-1345. doi: 10.3934/math.2022079 |
[8] | Rizwan Rizwan, Jung Rye Lee, Choonkil Park, Akbar Zada . Switched coupled system of nonlinear impulsive Langevin equations with mixed derivatives. AIMS Mathematics, 2021, 6(12): 13092-13118. doi: 10.3934/math.2021757 |
[9] | Naimi Abdellouahab, Keltum Bouhali, Loay Alkhalifa, Khaled Zennir . Existence and stability analysis of a problem of the Caputo fractional derivative with mixed conditions. AIMS Mathematics, 2025, 10(3): 6805-6826. doi: 10.3934/math.2025312 |
[10] | Subramanian Muthaiah, Dumitru Baleanu, Nandha Gopal Thangaraj . Existence and Hyers-Ulam type stability results for nonlinear coupled system of Caputo-Hadamard type fractional differential equations. AIMS Mathematics, 2021, 6(1): 168-194. doi: 10.3934/math.2021012 |
A study was conducted on the existence of solutions for a class of nonlinear Caputo type higher-order fractional Langevin equations with mixed boundary conditions on a star graph with k+1 nodes and k edges. By applying a variable transformation, a system of fractional differential equations with mixed boundary conditions and different domains was converted into an equivalent system with identical boundary conditions and domains. Subsequently, the existence and uniqueness of solutions were verified using Krasnoselskii's fixed point theorem and Banach's contraction principle. In addition, the stability results of different types of solutions for the system were further discussed. Finally, two examples are illustrated to reinforce the main study outcomes.
The field of fractional calculus, which focuses on the application of fractional derivatives, has been rapidly developing in recent years. Compared to traditional integer calculus, fractional calculus has a broader range of applicability in both temporal and spatial scales, enabling more accurate descriptions of real-world problems. As an important branch of fractional calculus, fractional differential equations (FDEs) contain fractional derivatives and have been widely applied in various fields, including chemistry, physics, electrical engineering, economics, and biology[1,2,3]. These equations hold significant practical value and have had a profound impact on the theoretical development of calculus, serving as one of the key foundations in its research. Currently, boundary value problems (BVPs) of FDEs are a hot topic of study. Scholars have mainly used fixed point theory [4,5,6,7,8], such as the Banach fixed point theorem, Schaefer fixed point theorem, and Krasnoselskii fixed point theorem, to establish sufficient conditions for the existence and uniqueness (EU) of FDEs solutions. These achievements have been highly important for deepening our understanding of FDEs and promoting their practical applications.
Fractional differential equations are of great significance in describing actual network structures, such as pipelines, gas pipelines, molecular structures, and computer network extensions. In 1980, Lumer[9] proposed the theory of differential equations on graphs based on the branching space framework, and this field has since been widely developed for application in multiple disciplines such as chemical engineering, biology, and physics. Therefore, researchers have a strong interest in the existence and stability of solutions to BVPs of differential equations and their fractional mathematical models on graphs.
Graet et al.[10] published their first work in the field in 2014, where they utilized known fixed point theorems to prove the EU of solutions to fractional BVPs on star graphs. That is, the authors studied a star graph ˜G=˜V(˜G)∪˜E(˜G), where ˜V={ϵ0,ϵ1,ϵ2} and ˜E={→ϵ1ϵ0,→ϵ2ϵ0} are sets of three vertices and of two edges, respectively; ϵ0 is the junction node and →ϵiϵ0 are the edges connecting nodes ϵi to ϵ0 with length ρi=|→ϵiϵ0| for i=1,2. The nonlinear fractional BVPs system on each edge →ϵiϵ0 in their work[10] is defined as follows:
{−Dα0φi=mi(t)Fi(t,φi),t∈(0,ρi),i=1,2,φ1(0)=φ2(0)=0,φ1(ρ1)=φ2(ρ2),Dβ0φ1(ρ1)+Dβ0φ2(ρ2)=0, | (1.1) |
where Dα0 and Dβ0 represent the Riemann-Liouville fractional derivative of orders α∈(1,2] and β∈(0,α), respectively; mi:[0,ρi]→R are continuous functions with mi(t)≠0 on [0,ρi], and Fi:[0,ρi]×R→R are continuous functions. The EU of solutions for the BVPs (1.1) are derived by applying Scheafer's fixed point theorem and the Banach contraction principle. In 2019, Mehandirata et al. [11] expanded upon Graef's earlier work by generalizing it to apply to star graphs comprising k+1 nodes and k edges as follows:
{CDα0φi(t)=Fi(t,φi(t),CDβ0ui(t)),t∈(0,ρi),i=1,2,⋯,k,φi(0)=0,∑ki=1φ′i(ρi)=0,i=1,2,⋯,k,φi(ρi)=φj(ρj),i,j=1,2,⋯,k,i≠j, | (1.2) |
where CDα0 and CDβ0 represent the Caputo fractional derivative of orders α∈(1,2] and β∈(0,α−1), Fi:[0,ρi]×R→R are continuous functions; ˜G=˜V(˜G)∪˜E(˜G) with ˜V(˜G)={ϵ0,ϵ1,⋯,ϵk} and ˜E(˜G)={ei=→ϵiϵ0,i=1,2,⋯,k}, ρi=|→ϵiϵ0|,i=1,2,⋯,k (a collection of k edges incident to a single node point (see Figure 1)). The EU of the solution to the BVPs (1.2) was proven using the same fixed-point theorem as in prior work[10].
The BVPs of FDEs on graphs have attracted widespread attention from scholars, and some interesting research results have been achieved[12,13,14,15,16,17,18,19]. For instance, in 2020, Etemad[12] proved the existence of solutions to fractional BVPs on ethane graphs using Schaefer's fixed point theorem and Krasnoselskii's fixed point theorem. In the same year, Mophou and Leugering[13] proved the EU of the solution through their study of the optimal control of fractional Sturm-Liouville BVPs on star graphs. In 2021, Turab[14] verified the existence of solutions to fractional BVPs on hexagonal graphs using Krasnoselskii's fixed point theorem and Schaefer's fixed point theorem. In Han's study[15], the Banach contraction mapping principle and Schaefer's fixed point theorem were applied to the EU of solutions for BVPs of nonlinear fractional differential equations on star graphs. In 2021, Ali [16] considered the existence of solutions to fractional BVPs on cyclohexane graphs. Additionally, Zhang et al.[17] studied the BVPs of fractional Langevin equations on star graphs as follows:
{CDα0,t(D+λi)φi(t)=Fi(t,φi(t),CDβ0,tφi(t)),t∈(0,ρi),i=1,2,⋯,k,φi(0)=0,∑ki=1φ′i(ρi)=0,i=1,2,⋯,k,φi(ρi)=φj(ρj),i,j=1,2,⋯,k,i≠j, | (1.3) |
where α∈(0,1) and β∈(0,α), λi∈R+, D is the ordinary derivative, Fi:[0,ρi]×R→R are continuous functions, and the two fractional operators CDα0 and CDβ0 denote the Caputo fractional derivatives. The[17] studied a star graph ˜G=˜V(˜G)∪˜E(˜G), where ˜V={ϵ0,ϵ1,⋯,ϵk} and ˜E={ei=→ϵiϵ0, i=1,2,⋯,k} are sets of k+1 nodes and set of k edges, with ρi=|→ϵiϵ0|. The author proved the EU of the BVP (1.3) solution by utilizing Schaefer's fixed point theorem and Banach contraction principle.
On the other hand, Ulam stability analysis was proposed by Ulam in the 1940s and further developed by Hyers. This analysis primarily studies whether the behavior of a system remains stable when there are slight changes in its parameters. Regarding Banach spaces, S. Banach introduced the famous fixed-point theorem in 1932. Later, Gleason, Ricciardi, and Ulam provided the theoretical foundation for Ulam stability by extending this theorem to additive mappings in metric spaces. In the field of FDEs, scholars began to study the stability of Ulam in the late 20th century and have achieved some notable results[20,21,22,23,24,25,26]. In 2017, Khan et al.[20] studied the Ulam stability of solutions to fractional differential equation systems using topological degree methods. In 2019, the same author [21] utilized the Guo-Krasnoselskii theorem to study the uniqueness of solutions and Ulam stability for differential equations containing Atangana-Baleanu-Caputo fractional derivatives. The same year, Devi et al.[22] proved the Ulam stability of specific FDEs and provided examples illustrating their application. More recently, Zhang et al.[23] studied the existence and Ulam-type stability of solutions to BVPs containing Caputo fractional derivatives on star graphs. These research studies show that the analysis of stability for solutions of FDEs is an active and important field of study with significant implications for understanding the long-term behavior of complex dynamic systems.
Inspired by the above-mentioned research[15,17,23], it can be seen that how to solve the mixed boundary conditions for a class of nonlinear higher-order fractional Langevin equations on a star graph consisting of k+1 nodes and k edges has not yet been examined. Specifically, this work examines the following problems:
{CDα0,t(D2+λi)φi(t)=Fi(t,φi(t),CDβ0,tφi(t)),t∈(0,ρi),i=1,2,⋯,k,φ′i(0)=φi(ρi)=0,∑ki=1φ″i(ρi)=0,i=1,2,⋯k,φ″i(ρi)=φ″j(ρj),i,j=1,2,⋯k,i≠j, | (1.4) |
where α∈(0,1) and β∈(0,α), λi∈R+, D2 is the ordinary second-order derivative, Fi:[0,ρi]×R→R are continuous functions, and the two fractional operators CDα0 and CDβ0 denote the Caputo fractional derivatives. The star graph is ˜G=˜V(˜G)∪˜E(˜G), where ˜V={ϵ0,ϵ1,⋯,ϵk} and ˜E={ei=→ϵiϵ0, i=1,2,⋯,k} are sets of k+1 nodes and set of k edges, and ρi=|→ϵiϵ0|. We consider a local coordinate system with ϵi as the origin and coordinates t in the interval (0,ρi).
This study investigates the existence, uniqueness, and Ulam stability of solutions to nonlinear fractional BVP (1.4). The EU of the solution to problem (1.4) can be demonstrated by utilizing Krasnoselskii's fixed point theorem and Banach's contraction mapping principle. Meanwhile, the Ulam stability of this system was verified using the matrix eigenvalue method. Compared with existing research results, the innovative results presented in this article can be summarized as follows: First, we extend the fractional Langevin equation on a star graph to higher-order fractional cases. Second, compared with other research[10,11,15,23], the Langevin equation in this paper introduces nonlocal terms, which increases the difficulty of prior estimation. Third, compared with another study[17], we not only investigated the existence and uniqueness of solutions to higher-order fractional Langevin equations, but also extended the relevant results on their Ulam stability. Fourth, compared with prior research[10,11,15,17,23], the fractional BVP (1.4) considered in this paper are more generalized and complex, as its nonlinear terms and boundary conditions depend not only on unknown functions, but also on fractional derivatives. Finally, Theorem 3.1 (see Section 3) proves that the problem (1.4) has at least one solution. This theorem proposes a linear growth condition for nonlinear terms, reduces the existence conditions, and thus makes the required existence condition more relaxed than condition (H3) used in previous literature [11,15].
The remaining parts of this manuscript are structured as follows. Section 2 proposes the auxiliary Lemma 2.5, which transforms the BVP (1.4) into an equivalent system (2.1), while reviewing the main relationships in fractional calculus. Section 3 proves the uniqueness and existence of solutions to the fractional differential BVP (1.4). Section 4 establishes sufficient conditions for the Ulam stability of the solution to system (2.1). Section 5 illustrates the main results of this paper regarding the existence, uniqueness, and Ulam stability of solutions through two examples. Finally, some conclusions are given in the last section.
In this section, we will revisit the concept of fractional calculus and outline some basic results that will provide a basis for the subsequent discussions in this paper.
Definition 2.1. [1]. Let f∈C([a,b],R). Then the Riemann-Liouville fractional integral is given by
Iαaf(τ)=1Γ(α)∫τa(τ−s)α−1f(s)ds,α>0,τ>a, |
where Γ(⋅) is the classical Euler gamma function.
Definition 2.2. [1]. Let f∈Cn([a,b],R). Then the Caputo fractional derivative operator of order α>0 is defined by
CDαa,τf(τ)=1Γ(n−α)∫τa(τ−s)n−α−1f(n)(s)ds,τ>a, |
where n−1<α≤n and n∈N.
Lemma 2.1. [1]. Let α>0. Suppose that u∈ACn[0,1]. Then
Iα0CDα0,τu(τ)=u(τ)+c1+c2τ+c3τ2+⋯+cnτn−1, |
where ci∈R,i=1,2,⋯n, n=[α]+1.
Lemma 2.2. [27]. Suppose that (Dnt)(τ) and (CDα+na,τt)(τ) exist. Then
(CDαa,τDnt)(τ)=(CDα+na,τt)(τ),α>0, |
where n∈N and D=d/dτ.
Lemma 2.3. [1]. If α>0, β>α−1, τ>0, then
CDα0,ττβ=Γ(β+1)Γ(β+1−α)τβ−α. |
Theorem 2.1 (Urs). [28] Suppose A is a square matrix of order n with positive real entries, i.e., A∈Mnn(R+). Then, the following statements are equivalent:
(i) The eigenvalues of matrix A (in the open unit disc), denoted by λ, ∀λ∈C with det(λI−A) = 0, i.e., |λ|<1;
(ii) The matrix (I−A) is nonsingular;
(iii) The matrix (I−A)−1 has nonnegative elements and (I−A)−1=I+A+⋯+An+⋯.
Theorem 2.2 (Krasnoselskii's fixed point theorem). [29]. Let P be a closed, bounded, convex, and nonempty subset of a Banach space Z. Let A and B be two operators such that
(a)Az+Bˉz∈P for all z,ˉz∈P,
(b)A is compact and continuous on P,
(c)B is a contraction mapping on P.
Then there exists ℏ∈P such that ℏ=Aℏ+Bℏ.
Lemma 2.4. [11]. Let α>0, φ be a function defined on [0,ρ], and z(τ)=φ(ρτ). Suppose that CDα0,tφ exists on [0,ρ], t∈[0,ρ], then
CDα0,tφ(t)=ρ−α(CDα0,tz(τ)),τ=t/ρ∈[0,1]. |
Lemma 2.5. Let α∈(n−1,n), φ be a function defined on [0,ρ], and z(τ)=φ(ρτ). Suppose that CDα0,tφ exists on [0,ρ], t∈[0,ρ], then
CDα0,t(D2+λ)φ(t)=ρ−α−2CDα0,τ(D2+λρ2)z(τ),τ=t/ρ∈[0,1]. |
Proof. By means of Definition 2.2 and Lemma 2.2, we obtain
CDα0,t(D2+λ)φ(t)=CDα+20,tφ(t)+λCDα0,tφ(t)=1Γ(n−α)∫t0(t−s)n−α−1φ(n+2)(s)ds+λΓ(n−α)∫t0(t−s)n−α−1φ(n)(s)ds=1Γ(n−α)∫ρτ0(ρτ−s)n−α+1φ(n+2)(s)ds+λΓ(n−α)∫ρτ0(ρτ−s)n−α−1φ(n)(s)ds(t=ρτ)=ρn−αΓ(n+2−α)∫τ0(τ−ˆs)n−α+1φ(n+2)(ρˆs)dˆs+λρn−αΓ(n−α)∫τ0(τ−ˆs)n−α−1φ(n)(ρˆs)dˆs(ˆs=s/ρ)=ρ−α−2Γ(n+2−α)∫τ0(τ−ˆs)n−α+1z(n+2)(ˆs)dˆs+λρ−αΓ(n−α)∫τ0(τ−ˆs)n−α−1z(n)(ˆs)dˆs(z(n)(τ)=ρnφ(n)(ρτ))=ρ−α−2CDα+20,τz(τ)+λρ−αCDα0,τz(τ)=ρ−α−2CDα0,τ(D2+λρ2)z(τ). |
This concludes the proof of Lemma 2.5.
Under the direct application of Lemmas 2.4 and 2.5, BVP (1.4) is equivalently transformed into system (2.1) defined on [0, 1], as given by
{CDα0,τ(D2+λiρ2i)zi(τ)=ρα+2ifi(τ,zi(τ),ρ−βiCDβ0,τzi(τ)),τ∈(0,1),z′i(0)=zi(1)=0,∑ki=1ρ−2iz″i(1)=0,i=1,2,⋯k,z″i(1)=z″j(1),i,j=1,2,⋯k,i≠j, | (2.1) |
where zi(τ)=φi(ρiτ), fi(τ,u,v)=Fi(ρiτ,u,v).
Lemma 2.6. Let hi(τ)∈C[0,1], α∈(0,1). Then zi(τ) is a solution of the BVP
{CDα0,τ(D2+λiρ2i)zi(τ)=hi(τ),τ∈(0,1),i=1,2,⋯k,z′i(0)=zi(1)=0,∑ki=1ρ−2iz″i(1)=0,i=1,2,⋯k,z″i(1)=z″j(1),i,j=1,2,⋯k,i≠j, | (2.2) |
which is given by
zi(τ)=1Γ(α+2)∫τ0(τ−s)α+1hi(s)ds−1Γ(α+2)∫10(1−s)α+1hi(s)ds+λiρ2i∫10(1−s)zi(s)ds−λiρ2i∫τ0(τ−s)zi(s)ds+(1−τ2)k∑j=1ℓj(1Γ(α)∫10(1−s)α−1hj(s)ds−λjρ2jzj(1))+(1−τ2)k∑j=1,j≠iℓj(λjρ2jzj(1)−λiρ2izi(1))−(1−τ2)k∑j=1,j≠iℓj(1Γ(α)∫10(1−s)α−1(hj(s)−hi(s))ds), | (2.3) |
where ℓj=ρ−2j2k∑j=1ρ−2j,j=1,2,⋯k.
Proof. Applying the integral operator Iα+20 to (2.2) and using Lemma 2.1, we have
zi(τ)=−λiρ2i∫τ0(τ−s)zi(s)ds+Iα+20hi(τ)−a(1)i−a(2)iτ−a(3)iτ2,i=1,2,⋯,k, | (2.4) |
where aji(i=1,2,⋯,k,j=1,2,3) are some constants. Deriving both sides of Eq (2.4) from 0 to τ gives
z′i(τ)=−λiρ2i∫τ0zi(s)ds+Iα+10hi(τ)−a(2)i−2τa(3)i |
and
z″i(τ)=−λiρ2izi(τ)+Iα0hi(τ)−2a(3)i. |
z′i(0)=0 implies that a(2)i=0, which leads to
z′i(τ)=−λiρ2i∫τ0zi(s)ds+Iα+10hi(τ)−2τa(3)i. |
Since z″i(1)=z″j(1) and ∑ki=1ρ−2iz″i(1)=0, we obtain
−λiρ2izi(1)+Iα0hi(τ)|τ=1−2a(3)i=−λjρ2jzj(1)+Iα0hj(τ)|τ=1−2a(3)j,i≠j | (2.5) |
and
∑ki=1ρ−2i(−λiρ2izi(1)+Iα0hi(τ)|τ=1−2a(3)i)=0. | (2.6) |
According to (2.5) and (2.6), there is
2k∑j=1ρ−2ja(3)i=k∑j=1ρ−2j(−λjρ2jzj(1)+Iα0hj(τ)|τ=1)−k∑j=1,j≠iρ−2j(−λjρ2jzj(1)+λiρ2izi(1)+Iα0hj(τ)|τ=1−Iα0hi(τ)|τ=1), |
which implies
a(3)i=−k∑j=1,j≠iℓj(−λjρ2jzj(1)+λiρ2izi(1)+Iα0hj(τ)|τ=1−Iα0hi(τ)|τ=1)+k∑j=1ℓj(−λjρ2jzj(1)+Iα0hj(τ)|τ=1). | (2.7) |
By substituting zi(1)=0 and a(3)i into in (2.4), we get
a(1)i=Iα+20hi(τ)|τ=1−λiρ2i∫10(1−s)zi(s)ds−k∑j=1ℓj(−λjρ2jzj(1)+Iα0hj(τ)|τ=1)+k∑j=1,j≠iℓj(−λjρ2jzj(1)+λiρ2izi(1)+Iα0hj(τ)|τ=1−Iα0hi(τ)|τ=1). | (2.8) |
Inserting the values from (2.7) and (2.8) into (2.4), we get the solution (2.3). This completes the proof.
In this section, we prove the existence and uniqueness of the solution to system (2.1). We first define a Banach space X={z:z,CDβ0,τz∈C[0,1]}, with the supremum norm
‖z‖X=‖z‖+‖CDβ0,τz‖, |
where ‖z‖=maxτ∈[0,1]|z(τ)|,‖CDβ0,τz‖=maxτ∈[0,1]|CDβ0,τz(τ)|. It is obvious that the product space (Xk=X1×X2×⋯×Xk,‖⋅‖Xk) is a Banach space, where the norm is defined by
‖(z1,z2,⋯,zk)‖Xk=∑ki=1‖zi‖X,(z1,z2,⋯,zk)∈Xk. |
By considering Lemma 2.6, we introduce the operator T:Xk→Xk, related to system (2.1) by
T(z1,z2,⋯,zk)(τ)=(T1(z1,z2,⋯,zk)(τ),T2(z1,z2,⋯,zk)(τ)⋯,Tk(z1,z2,⋯,zk)(τ)), |
for τ∈[0,1] and zi∈X,i=1,2,⋯k, where
Ti(z1,z2,⋯,zk)(τ)=ρα+2iΓ(α+2)∫τ0(τ−s)α+1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds−ρα+2iΓ(α+2)∫10(1−s)α+1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds+λiρ2i∫10(1−s)zi(s)ds−λiρ2i∫τ0(τ−s)zi(s)ds+(1−τ2)k∑j=1,j≠iℓj(λjρ2jzj(1)−λiρ2izi(1))+(1−τ2)k∑j=1ℓj(ρα+2jΓ(α)∫10(1−s)α−1fj(s,zj(s),ρ−βjCDβ0,szj(s))ds−λjρ2jzj(1))+(1−τ2)k∑j=1,j≠iℓjρα+2iΓ(α)∫10(1−s)α−1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds−(1−τ2)k∑j=1,j≠iℓjρα+2jΓ(α)∫10(1−s)α−1fj(s,zj(s),ρ−βjCDβ0,szj(s))ds. | (3.1) |
Assume that the following conditions hold:
(H1) The functions fi:[0,1]×R2→R are continuous, i=1,2,⋯,k.
(H2) There exist functions ξi(τ),ηi(τ),ψi(τ)∈C([0,1],[0,+∞)), such that
|fi(τ,u,v)|≤ξi(τ)+ηi(τ)|u(τ)|+ψi(τ)|v(τ)|,i=1,2,⋯,k, |
for all τ∈[0,1] and u,v∈R2.
(H3) There exist functions wi(τ)∈C([0,1],[0,+∞)), such that
|fi(τ,u,v)−fi(τ,u1,v1)|≤wi(τ)(|u−u1|+|v−v1|),i=1,2,⋯,k, |
for all τ∈[0,1] and (u,v),(u1,v1)∈R2.
For the convenience of calculation, the following symbols are given:
Q1=2Γ(α+3)+2Γ(α+1)+1Γ(α−β+3)+4Γ(α+1)Γ(3−β),Q2=2Γ(α+1)+4Γ(α+1)Γ(3−β). |
Theorem 3.1. Assume that (H1) and (H2) hold, then system (2.1) allows at least one solution on [0, 1], provided that
k∑i=1θi<1, |
where
θi=[Δi(η∗i+ρ−βiψ∗i)+Ωi+k∑j=1,j≠i(˜Δj(η∗j+ρ−βjψ∗j)+˜Ωj)] |
and
Δi=Q1ρα+2i,Ωi=3λiρ2i+5λiρ2iΓ(3−β),˜Ωj=2λjρ2j+4λjρ2jΓ(3−β),˜Δj=Q2ρα+2j,ξ∗i=maxτ∈[0,1]|ξi(τ)|,η∗i=maxτ∈[0,1]|ηi(τ)|,ψ∗i=maxτ∈[0,1]|ψi(t)|. |
Proof. Let Θ={z=(z1,z2,⋯zk)∈Xk:‖zi‖X≤r}, where r is chosen such that
r≥∑ki=1(Δiξ∗i+∑kj=1,j≠i˜Δjξ∗j)(1−∑ki=1θi), | (3.2) |
then Θ is a bounded and closed convex subset of the Banach space Xk. We define Ai and Bi on Θ as
Ai(z1,z2,⋯,zk)(τ)=(A1(z1,z2,⋯,zk)(τ),A2(z1,z2,⋯,zk)(τ)⋯,Ak(z1,z2,⋯,zk)(τ)),Bi(z1,z2,⋯,zk)(τ)=(B1(z1,z2,⋯,zk)(τ),B2(z1,z2,⋯,zk)(τ)⋯,Bk(z1,z2,⋯,zk)(τ)), |
where
Ai(z1,z2,⋯,zk)(τ)=ρα+2iΓ(α+2)∫τ0(τ−s)α+1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds−ρα+2iΓ(α+2)∫10(1−s)α+1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds+(1−τ2)k∑j=1ℓjρα+2jΓ(α)∫10(1−s)α−1fj(s,zj(s),ρ−βjCDβ0,szj(s))ds+(1−τ2)k∑j=1,j≠iℓjρα+2iΓ(α)∫10(1−s)α−1fi(s,zi(s),ρ−βiCDβ0,szi(s))ds−(1−τ2)k∑j=1,j≠iℓjρα+2jΓ(α)∫10(1−s)α−1fj(s,zj(s),ρ−βjCDβ0,szj(s))ds |
and
Bi(z1,z2,⋯,zk)(τ)=λiρ2i∫10(1−s)zi(s)ds−λiρ2i∫τ0(τ−s)zi(s)ds+(1−τ2)k∑j=1,j≠iℓj(λjρ2jzj(1)−λiρ2izi(1))−(1−τ2)k∑j=1ℓjλjρ2jzj(1), |
for all τ∈[0,1] and z=(z1,z2,⋯,zk)∈Θ.
Now, for every z=(z1,z2,⋯,zk),ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈Xk, we have
|(Aiz+Biˉz)(τ)|≤2ρα+2iΓ(α+2)∫10(1−s)α+1|fi(s,zi(s),ρ−βiCDβ0,szi(s))|ds+k∑j=1ℓj(ρα+2jΓ(α)∫10(1−s)α−1|fj(s,zj(s),ρ−βjCDβ0,szj(s))|ds+λjρ2j|ˉzj(1)|)+2λiρ2i∫10(τ−s)|ˉzi(s)|ds+k∑j=1,j≠iℓj(λjρ2j|ˉzj(1)|+λiρ2i|ˉzj(s)|)+k∑j=1,j≠iℓjρα+2jΓ(α)∫10(1−s)α−1|fj(s,zj(s),ρ−βjCDβ0,szj(s))|ds+k∑j=1,j≠iℓjρα+2iΓ(α)∫10(1−s)α−1|fi(s,zi(s),ρ−βiCDβ0,szi(s))|ds≤2ρα+2iΓ(α+3)(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)+λiρ2i‖ˉzi‖+k∑j=1λjρ2j‖ˉzj‖+k∑j=1ρα+2jΓ(α+1)(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+λiρ2i‖ˉzi‖+1Γ(α+1)k∑j=1,j≠iρα+2j(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+k∑j=1,j≠iλjρ2j‖ˉzj‖+ρα+2iΓ(α+1)(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)≤2ρα+2iΓ(α+3)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)+λiρ2i‖ˉzi‖X+k∑j=1λjρ2j‖ˉzj‖X+k∑j=1,j≠iλjρ2j‖ˉzj‖X+λiρ2i‖ˉzi‖X+k∑j=1ρα+2jΓ(α+1)(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)+k∑j=1,j≠iρα+2jΓ(α+1)(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)+ρα+2iΓ(α+1)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X). |
From this we can deduce the following:
‖(Aiz+Biˉz)(τ)‖≤(2Γ(α+1)+2Γ(α+3))ρα+2i(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)+3λiρ2i‖ˉzi‖X+k∑j=1,j≠i2ρα+2jΓ(α+1)(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)+2k∑j=1,j≠iλjρ2j‖ˉzj‖X≤[(2Γ(α+1)+2Γ(α+3))ρα+2i(η∗i+ρ−βiψ∗i)+3λiρ2i+k∑j=1,j≠i(2ρα+2jΓ(α+1)(η∗j+ρ−βjψ∗j)+2λjρ2j)]r+(2Γ(α+1)+2Γ(α+3))ρα+2iξ∗i+k∑j=1,j≠i2ρα+2jξ∗jΓ(α+1). | (3.3) |
By Lemma 2.3 and (H2), we also can get
|CDβ0,τAiz(τ)+CDβ0,τBiˉz(τ)|≤ρα+2iΓ(α−β+2)∫τ0(τ−s)α−β+1|fi(s,zi(s),ρ−βiCDβ0,szi(s))|ds+λiρ2iΓ(2−β)∫τ0(τ−s)1−β|ˉzi(s)|ds+2τ2−βΓ(3−β)k∑j=1ℓjλjρ2j|ˉzj(1)|+2τ2−βΓ(α)Γ(3−β)k∑j=1ℓjρα+2j∫10(1−s)α−1|fj(s,zj(s),ρ−βjCDβ0,szj(s))|ds+2t2−βΓ(3−β)k∑j=1,j≠iℓjλjρ2j|ˉzj|+2τ2−βΓ(3−β)λiρ2i|ˉzi|+2τ2−βΓ(α)Γ(3−β)k∑j=1,j≠iℓjρα+2j∫10(1−s)α−1|fj(s,zj(s),ρ−βjCDβ0,szj(s))|ds+2τ2−βΓ(α)Γ(3−β)ℓiρα+2i∫10(1−s)α−1|fi(s,zi(s),ρ−βiCDβ0,szi(s))|ds≤ρα+2iΓ(α−β+3)(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)+λiρ2iΓ(3−β)‖ˉzi‖+2Γ(α+1)Γ(3−β)k∑j=1ρα+2j(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+2Γ(3−β)k∑j=1λjρ2j‖ˉzj‖+2Γ(3−β)k∑j=1,j≠iλjρ2j‖ˉzj‖+2λiρ2i‖ˉzi‖Γ(3−β)+2Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2j(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+2ρα+2iΓ(α+1)Γ(3−β)(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖). |
By using similar computations, we obtain
‖CDβ0,τ(Aiz+Biˉz)(τ)‖≤[(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))ρα+2i(η∗i+ρ−βiψ∗i)+5λiρ2iΓ(3−β)]‖zi‖X+k∑j=1,j≠i[(4Γ(α+1)Γ(3−β))ρα+2j(η∗j+ρ−βjψ∗j)+4λjρ2jΓ(3−β)]‖zj‖X+(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))ρα+2iξ∗i+4Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2jξ∗j≤[(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))ρα+2i(η∗i+ρ−βiψ∗i)+5λiρ2iΓ(3−β)+k∑j=1,j≠i(4Γ(α+1)Γ(3−β)ρα+2j(η∗j+ρ−βjψ∗j)+4λjρ2jΓ(3−β))]r+(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))ρα+2iξ∗i+4Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2jξ∗j. | (3.4) |
From (3.3) and (3.4), we get
‖Tz‖X=‖(Aiz+Biˉz)(τ)‖+‖CDβ0,τ(Aiz+Biˉz)(τ)‖≤[Q1ρα+2i(η∗i+ρ−βiψ∗i)+Ωi+k∑j=1,j≠i(Q2ρα+2j(η∗j+ρ−βjψ∗j)+˜Ωj))]r+Q1ρα+2iξ∗i+k∑j=1,j≠iQ2ρα+2jξ∗j≤[Δi(η∗i+ρ−βiψ∗i)+Ωi+k∑j=1,j≠i(˜Δj(η∗j+ρ−βjψ∗j)+˜Ωj)]r+Δiξ∗i+k∑j=1,j≠i˜Δjξ∗j≤θir+Ni, |
where
Ni=Δiξ∗i+k∑j=1,j≠i˜Δjξ∗j,i=1,2⋯k. |
Hence,
‖Tz‖Xk=k∑i=1‖Tiz‖X≤k∑i=1θir+k∑i=1Ni≤r, |
and so Ai(z)+Bi(ˉz)∈Θ.
On the other hand, the continuity of Ai follows from the continuity of functions fi(i=1,2,⋯,k). Now, we show that the operator Ai is uniformly bounded. For this, note that
|(Aiz(τ)+CDβ0,τAiz(τ)|≤[Q1ρα+2i(η∗i+ρ−βiψ∗i)+k∑j=1,j≠i(Q2ρα+2j(η∗j+ρ−βjψ∗j))]r+Q1ρα+2iξ∗i+k∑j=1,j≠iQ2ρα+2jξ∗j≤[Δi(η∗i+ρ−βiψ∗i)+k∑j=1,j≠i˜Δj(η∗j+ρ−βjψ∗j)]r+Δiξ∗i+k∑j=1,j≠i˜Δjξ∗j. |
This shows that the operator Ai is uniformly bounded on Θ.
Now, we show that the operator Ai is compact on Θ. Let τ1,τ2∈(0,1), τ1<τ2, then we have
|Aiz(τ2)−Aiz(τ1)|=ρα+2iΓ(α+2)∫τ10((τ2−s)α+1−(τ1−s)α+1)ds(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)+ρα+2iΓ(α+2)∫τ2τ1(τ2−s)α+1ds(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)+(τ22−τ21)k∑j=1(ρα+2jΓ(α+1)(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖))+(τ22−τ21)k∑j=1,j≠iρα+2jΓ(α+1)(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+(τ22−τ21)ρα+2iΓ(α+1)(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)≤ρα+2i(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)Γ(α+3)(τα+22−τα+21)+1Γ(α+1)k∑j=1ρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ22−τ21)+1Γ(α+1)ρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ22−τ21)+ρα+2i(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)Γ(α+1)(τ22−τ21) | (3.5) |
and
|CDβ0,τAiz(τ2)−CDβ0,τAiz(τ1)|≤ρα+2i(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)Γ(α−β+2)∫τ10((τ2−s)α−β+1−(τ1−s)α−β+1)ds−ρα+2i(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)Γ(α−β+2)∫τ2τ1(τ2−s)α−β+1ds+2(τ2−β2−τ2−β1)Γ(α+1)Γ(3−β)k∑j=1ρα+2j(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+2(τ2−β2−τ2−β1)Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2j(ξ∗j+η∗j‖zj‖+ρ−βjψ∗j‖CDβ0,τzj‖)+2(τ2−β2−τ2−β1)Γ(α+1)Γ(3−β)ρα+2i(ξ∗i+η∗i‖zi‖+ρ−βiψ∗i‖CDβ0,τzi‖)≤ρα+2iΓ(α−β+3)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)(τα−β+22−τα−β+21)+2Γ(α+1)Γ(3−β)k∑j=1ρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ2−β2−τ2−β1)+2ρα+2iΓ(α+1)Γ(3−β)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)(τ2−β2−τ2−β1)+2Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ2−β2−τ2−β1). | (3.6) |
From (3.5) and (3.6), we get
‖Aiz(τ2)−Aiz(τ1)‖X≤(2ρα+2i(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)Γ(α+1))(τ22−τ21)+ρα+2i(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)Γ(α+3)(τα+22−τα+21)+ρα+2iΓ(α−β+3)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)(τα−β+22−τα−β+21)+4ρα+2iΓ(α+1)Γ(3−β)(ξ∗i+(η∗i+ρ−βiψ∗i)‖zi‖X)(τ2−β2−τ2−β1)+2Γ(α+1)k∑j=1,j≠iρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ22−τ21)+4Γ(α+1)Γ(3−β)k∑j=1,j≠iρα+2j(ξ∗j+(η∗j+ρ−βjψ∗j)‖zj‖X)(τ2−β2−τ2−β1), |
which implies ‖Aiz(τ2)−Aiz(τ1)‖X→0 as τ2→τ1, and so ‖Aiz(τ2)−Aiz(τ1)‖Xk→0 as τ2→τ1. Thus, Ai is equicontinuous and, by the Arzelˊa-Ascoli theorem, we conclude that the operator Ai is a completely continuous operator.
Next, we prove that the operator Bi is a contraction. Letting z,ˉz∈Θ, we have
|Biz(τ)−Biˉz(τ)|≤λiρ2i∫τ0(τ−s)|ˉzi(s)−ˉzi(s)|ds+λiρ2i∫10(1−s)|ˉzi(s)−ˉzi(s)|ds+(1−τ2)k∑j=1ℓjλjρ2j|zj(1)−ˉzj(1)|+(1−τ2)k∑j=1,j≠iℓjλjρ2j|zj(1)−ˉzj(1)|+(1−τ2)k∑j=1,j≠iℓjλiρ2i|zi(1)−ˉzi(1)|≤3λiρ2i‖zi−ˉzi‖+2k∑j=1,j≠iλjρ2j‖zj−ˉzj‖ | (3.7) |
and
|CDβ0,τBiz(τ)−CDβ0,τBiˉz(τ)|≤λiρ2iΓ(2−β)∫τ0(τ−s)1−β|zi(s)−ˉzi(s)|ds+2τ2−βΓ(3−β)k∑j=1ℓjλjρ2j|zj−ˉzj|+2τ2−βΓ(3−β)k∑j=1,j≠iℓjλjρ2j|zj−ˉzj|+2τ2−βΓ(3−β)k∑j=1,j≠iℓjλiρ2i|zi−ˉzi|≤λiρ2iΓ(3−β)‖zi−ˉzi‖+2Γ(3−β)k∑j=1λjρ2j‖zj−ˉzj‖+2Γ(3−β)k∑j=1,j≠iλjρ2j‖zj−ˉzj‖+2λiρ2iΓ(3−β)‖zi−ˉzi‖. | (3.8) |
Thus, from (3.7) and (3.8), we get
‖Biz−Biˉz‖X=‖Biz−Biˉz‖+‖CDβ0,τBiz−CDβ0,τBiˉz‖≤(3λiρ2i+5λiρ2iΓ(3−β))‖zi−ˉzi‖X+k∑j=1,j≠i(2λjρ2j+4λjρ2jΓ(3−β))‖zj−ˉzj‖X≤Lik∑j=1‖zj−ˉzj‖X. |
Furthermore, we obtain
‖Biz−Bi¯z‖Xk=k∑i=1‖Biz−Biˉz‖X≤k∑i=1Li‖zj−ˉzj‖Xk. |
k∑i=1Li<1, which means that Θ is bounded. We use Theorem 2.2 to show that the operator T at least has one fixed point, and then system (2.1) has at least one solution.
Theorem 3.2. Assume that (H1) and (H3) hold. Then system (2.1) has a unique solution on [0, 1], that is,
(k∑i=1Ki)(k∑i=1Wi)+k∑i=1Li<1, | (3.9) |
where
Ki=Q1(ρα+2i+ρα−β+2i)+Q2k∑j=1,j≠i(ρα+2j+ρα−β+2j),Wi=maxτ∈[0,1]|wi(τ)|,Li=3λiρ2i+5λiρ2iΓ(3−β)+k∑j=1,j≠i(2λjρ2j+4λjρ2jΓ(3−β)). |
Proof. We will prove that T is a contraction mapping. For any z=(z1,z2,⋯,zk), ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈Xk, τ∈[0,1]. By Eq (3.1), we get
|Tiz(τ)−Tiˉz(τ)|≤ρα+2iΓ(α+2)∫τ0(τ−s)α+1|˜fi(s)|ds+ρα+2iΓ(α+2)∫10(1−s)α+1|˜fi(s)|ds+λiρ2i∫τ0(τ−s)|zi(s)−ˉzi(s)|ds+λiρ2i∫10(1−s)|zi(s)−ˉzi(s)|ds+(1−τ2)k∑j=1ℓjρα+2jΓ(α)∫10(1−s)α−1|˜fj(s)|ds+(1−τ2)k∑j=1ℓjλjρ2j|zj(1)−ˉzj(1)|+(1−τ2)k∑j=1,j≠iℓjλjρ2j|zj(1)−ˉzj(1)|+(1−τ2)k∑j=1,j≠iℓjλiρ2i|zi(1)−ˉzi(1)|+(1−τ2)k∑j=1,j≠iℓjρα+2jΓ(α)∫10(1−s)α−1|˜fj(s)|ds+(1−τ2)k∑j=1,j≠iℓjρα+2iΓ(α)∫10(1−s)α−1|˜fj(s)|ds, |
where
˜fi=fi(s,zi(s),ρ−βiCDβ0,szi(s))−fi(s,ˉzi(s),ρ−βiCDβ0,sˉzi(s)),˜fj=fj(s,zj(s),ρ−βjCDβ0,szj(s))−fj(s,ˉzj(s),ρ−βjCDβ0,sˉzj(s)),i=1,2,⋯,k. |
Now using assumption (H3) and 1−τ2<1(0<τ<1), ℓj∈(0,1), j=1,2,⋯,k, we have
|Tiz(τ)−Tiˉz(τ)|≤2ρα+2iΓ(α+3)Wi‖zi−ˉzi‖+2ρα−β+2iΓ(α+3)Wi‖CDβ0,szi−CDβ0,sˉzi‖+λiρ2i‖zi−ˉzi‖+k∑j=1λjρ2j‖zj−ˉzj‖+k∑j=1ρα+2jWjΓ(α+1)‖zj−ˉzj‖+k∑j=1ρα−β+2jWjΓ(α+1)‖CDβ0,szj−CDβ0,sˉzj‖+k∑j=1,j≠iλjρ2j‖zj−ˉzj‖+k∑j=1,j≠iλiρ2i‖zi−ˉzi‖+k∑j=1,j≠iρα+2jWjΓ(α+1)‖zj−ˉzj‖+k∑j=1,j≠iρα+2iWiΓ(α+1)‖zi−ˉzi‖+k∑j=1,j≠iρα−β+2jWjΓ(α+1)‖CDβ0,szj−CDβ0,sˉzj‖+k∑j=1,j≠iρα−β+2iWiΓ(α+1)‖CDβ0,szi−CDβ0,sˉzi‖≤2WiΓ(α+3)(ρα+2i+ρα−β+2i)(‖zi−ˉzi‖+‖CDβ0,szi−CDβ0,sˉzi‖)+3λiρ2i‖zi−ˉzi‖+2k∑j=1,j≠iλjρ2j‖zj−ˉzj‖+WiΓ(α+1)(ρα+2i+ρα−β+2i)(‖zi−ˉzi‖+‖CDβ0,szi−CDβ0,sˉzi‖)+1Γ(α+1)k∑j=1(ρα+2j+ρα−β+2j)Wj(‖zj−ˉzj‖+‖CDβ0,szj−CDβ0,sˉzj‖)+1Γ(α+1)k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj(‖zj−ˉzj‖+‖CDβ0,szj−CDβ0,sˉzj‖). |
Hence, for any z,ˉz∈Xk, we obtain
‖Tiz−Tiˉz‖≤(2Γ(α+3)+2Γ(α+1))(ρα+2i+ρα−β+2i)Wi‖zi−ˉzi‖X+3λiρ2i‖zi−ˉzi‖X+2k∑j=1,j≠iλjρ2j‖zj−ˉzj‖X+2Γ(α+1)k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj‖zj−ˉzj‖X. | (3.10) |
On the other hand, using Lemma 2.3,
|CDβ0,τTiz(τ)−CDβ0,τTiˉz(τ)|≤ρα+2iΓ(α−β+2)∫τ0(τ−s)α−β+1|˜fi(s)|ds+λiρ2iΓ(2−β)∫τ0(τ−s)1−β|zi(s)−ˉzi(s)|ds+2τ2−βΓ(3−β)k∑j=1ℓjλjρ2j|zj−ˉzj|+2τ2−βΓ(α)Γ(3−β)k∑j=1ℓjρα+2j∫10(1−s)α−1|˜fj(s)|ds+2τ2−βΓ(3−β)k∑j=1,j≠iℓjλjρ2j|zj−ˉzj|+2τ2−βΓ(3−β)k∑j=1,j≠iℓjλiρ2i|zi−ˉzi|+2τ2−βΓ(α)Γ(3−β)k∑j=1,j≠iℓjρα+2j∫10(1−s)α−1|˜fj(s)|ds+2τ2−βℓjρα+2iΓ(α)Γ(3−β)k∑j=1,j≠i∫10(1−s)α−1|˜fi(s)|ds, |
by using similar computations, we get
|CDβ0,τTiz(τ)−CDβ0,τTiˉz(τ)|≤(ρα+2i+ρα−β+2i)Γ(α−β+3)Wi(‖zi−ˉzi‖+‖CDβ0,szi−CDβ0,sˉzi‖)+λiρ2iΓ(3−β)‖zi−ˉzi‖+2Γ(3−β)k∑j=1λjρ2j‖zj−ˉzj‖+2Γ(3−β)k∑j=1,j≠iλjρ2j‖zj−ˉzj‖+2λiρ2iΓ(3−β)‖zi−ˉzi‖+2Γ(α+1)Γ(3−β)k∑j=1(ρα+2j+ρα−β+2j)Wj(‖zj−ˉzj‖+‖CDβ0,szj−CDβ0,sˉzj‖)+2Γ(α+1)Γ(3−β)k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj(‖zj−ˉzj‖+‖CDβ0,szj−CDβ0,sˉzj‖)+2Γ(α+1)Γ(3−β)(ρα+2i+ρα−β+2i)Wi(‖zi−ˉzi‖+‖CDβ0,szi−CDβ0,sˉzi‖), |
this implies that, for any z,ˉz∈Xk,
‖CDβ0,τTiz−CDβ0,τTiˉz‖≤(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))(ρα+2i+ρα−β+2i)Wi‖zi−ˉzi‖X+5λiρ2iΓ(3−β)‖zi−ˉzi‖X+4Γ(3−β)k∑j=1,j≠iλjρ2j‖zj−ˉzj‖X+4Γ(α+1)Γ(3−β)k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj‖zj−ˉzj‖X. | (3.11) |
It follows from (3.10) and (3.11) that
‖Tiz−Tiˉz‖X=‖Tiz−Tiˉz‖+‖CDβ0,τTiz−CDβ0,τTiˉz‖≤(2Γ(α+3)+2Γ(α+1)+1Γ(α−β+3)+4Γ(α+1)Γ(3−β))(ρα+2i+ρα−β+2i)Wi‖zi−ˉzi‖X+(3λiρ2i+5λiρ2iΓ(3−β))‖zi−ˉzi‖X+k∑j=1,j≠i(2λjρ2j+4λjρ2jΓ(3−β))‖zj−ˉzj‖X+(2Γ(α+1)+4Γ(α+1)Γ(3−β))k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj‖zj−ˉzj‖X≤Q1(ρα+2i+ρα−β+2i)Wi‖zi−ˉzi‖X+(3λiρ2i+5λiρ2iΓ(3−β))‖zi−ˉzi‖X+k∑j=1,j≠i(2λjρ2j+4λjρ2jΓ(3−β))‖zj−ˉzj‖X+Q2k∑j=1,j≠i(ρα+2j+ρα−β+2j)Wj‖zj−ˉzj‖X. |
From this it follows that
‖Tiz−Tiˉz‖X≤(Q1(ρα+2i+ρα−β+2i)+Q2k∑j=1,j≠i(ρα+2j+ρα−β+2j))(k∑i=1Wi)k∑j=1‖zj−ˉzj‖X+(3λiρ2i+3λiρ2iΓ(3−β)+k∑j=1,j≠i(2λjρ2j+4λjρ2jΓ(3−β)))k∑j=1‖zj−ˉzj‖X=(Kik∑i=1Wi+Li)k∑j=1‖zj−ˉzj‖X. |
As a consequence, we obtain
‖Tiz−Tiˉz‖Xk=k∑i=1‖Tiz−Tiˉz‖X≤(k∑i=1Ki(k∑i=1Wi)+k∑i=1Li)‖zj−ˉzj‖Xk, |
which, given condition (3.9), proves that operator T is a contraction. This implies that T has a unique fixed point on Xk, that is, system (2.1) has a unique solution on [0, 1].
In this section, we introduce Ulam type stability concepts for system (2.1). Let εi>0, fi:[0,1]×R2→R be continuous, and Φi(τ):[0,1]→R+(τ∈[0,1]) be nondecreasing. Consider the following inequalities:
|CDα0,τ(D2+λiρ2i)zi(τ)−ρα+2ifi(τ,zi(τ),ρ−βiCDβ0,τzi(τ))|≤εi,i=1,2,⋯,k, | (4.1) |
|CDα0,τ(D2+λiρ2i)zi(τ)−ρα+2ifi(τ,zi(τ),ρ−βiCDβ0,τzi(τ))|≤Φi(τ)εi,i=1,2,⋯,k, | (4.2) |
|CDα0,τ(D2+λiρ2i)zi(τ)−ρα+2ifi(τ,zi(τ),ρ−βiCDβ0,τzi(τ))|≤Φi(τ),i=1,2,⋯,k. | (4.3) |
Definition 4.1. [23] System (2.1) is Ulam-Hyers stable if there exists a real number cf1,f2,⋯,fk>0 such that, for each ε=ε(ε1,ε2,⋯,εk)>0 and for each solution z=(z1,z2,⋯,zk)∈X of inequalities (4.1), there exists a solution ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈X of system (2.1) with
‖z−ˉz‖X≤cf1,f2,⋯,fkε,τ∈[0,1]. |
Definition 4.2. [23] System (2.1) is generalized Ulam-Hyers stable if there exists a function Υf1,f2,⋯,fk∈C(R+,R+) with Υf1,f2,⋯,fk(0)=0 such that, for each ε=ε(ε1,ε2,⋯,εk)>0 and for each solution v=(z1,z2,⋯,zk)∈X of inequalities (4.2), there exists a solution ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈X of system (2.1) with
‖z−ˉz‖X≤Υf1,f2,⋯,fk(ε),τ∈[0,1]. |
Definition 4.3. [23] System (2.1) is Ulam-Hyers-Rassias stable with respect to Φ=Φ(Φ1,Φ2,⋯,Φk)∈C([0,1],R+) if there exists a real number cf1,f2,⋯,fkΦ>0 such that, for every ε=ε(ε1,ε2,⋯,εk)>0 and for each solution z=(z1,z2,⋯,zk)∈X of inequalities (4.2), there exists a solution ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈X of system (2.1) with
‖z−ˉz‖X≤cf1,f2,⋯,fk,φεΦ(τ),τ∈[0,1]. |
Definition 4.4. [23] System (2.1) is generalized Ulam-Hyers-Rassias stable with respect to Φ=Φ(Φ1,Φ2,⋯,Φk)∈C([0,1],R+) if there exists a real number cf1,f2,⋯,fkΦ>0 such that, for each solution z=(z1,z2,⋯,zk)∈X of inequalities (4.2), there exists a solution ˉz=(ˉz1,ˉz2,⋯,ˉzk)∈X of system (2.1) with
‖z−ˉz‖X≤cf1,f2,⋯,fk,ΦΦ(τ),τ∈[0,1]. |
Remark 4.1. A function z=(z1,z2,⋯,zk)∈X is a solution of (4.1), if there exist functions ϕi∈C([0,1],R) which depend on zi such that
(i)|ϕi(τ)|≤εi,τ∈[0,1],i=1,2,⋯,k,
(ii)CDα0,τ(D2+λiρ2i)zi(τ)=ρα+2ifi(τ,zi(τ),ρ−βCiDβ0,τzi(τ))+ϕi(τ),τ∈[0,1],i=1,2,⋯,k.
One can make similar Remarks for inequalities (4.2) and (4.3).
Lemma 4.1. If z=(z1,z2,⋯,zk)∈X is a solution of inequality (4.1), then the following inequalities hold:
|zi(τ)−θi(τ)|≤(2Γ(α+3)+2Γ(α+1))εi+2Γ(α+1)k∑j=1,j≠iεj,i=1,2,⋯,k |
and
|CDβ0,τzi(τ)−CDβ0,τθi(τ)|≤(1Γ(α−β+3)+4Γ(α+1)Γ(3−β))εi+4Γ(α+1)Γ(3−β)k∑j=1,j≠iεj,i=1,2,⋯,k, |
where
θi(τ)=1Γ(α+2)∫τ0(τ−s)α+1hi(s)ds+1Γ(α+2)∫10(1−s)α+1hi(s)ds+λiρ2i∫10(1−s)θi(s)ds−λiρ2i∫τ0(τ−s)θi(s)ds+(1−τ2)k∑j=1ℓj(1Γ(α)∫10(1−s)α−1hj(s)ds−λjρ2jθj(1))+(1−τ2)k∑j=1,j≠iℓj(λjρ2jθj(1)−λiρ2iθi(1))−(1−τ2)k∑j=1,j≠iℓj(1Γ(α)∫10(1−s)α−1(hj(s)−hi(s))ds),i=1,2,⋯,k |
and
hi(s)=ρα+2ifi(s,zi(s),ρ−βiCDβ0,τzi(s)),i=1,2,⋯,k, |
hj(s)=ρα+2jfj(s,zj(s),ρ−βjCDβ0,τzj(s)),i=1,2,⋯,k. |
Proof. Given z is the solution of (4.1), then according to Remark 4.1 we have
{CDα0,τ(D2+λiρ2i)zi(τ)=ρα+2ifi(τ,zi(τ),ρ−βiCDβ0,τzi(τ))+ϕi(τ),i=1,2,⋯k,z′i(0)=zi(1)=0,∑ki=1ρ−2iz″i(1)=0,i=1,2,⋯k,ˉz″i(1)=z″j(1),i,j=1,2,⋯k,i≠j. | (4.4) |
By Lemma 2.6, the solution of (4.4) is given by
zi(τ)=1Γ(α+2)∫τ0(τ−s)α+1(hi(s)+ϕi(s))ds−1Γ(α+2)∫10(1−s)α+1(hi(s)+ϕi(s))ds+λiρ2i∫10(1−s)zi(s)ds−λiρ2i∫τ0(τ−s)zi(s)ds+(1−τ2)k∑j=1ℓj(1Γ(α)∫10(1−s)α−1(hj(s)+ϕj(s))ds−λjρ2jzj(1))+(1−τ2)k∑j=1,j≠iℓj(λjρ2jzj(1)−λiρ2izi(1))+(1−τ2)k∑j=1,j≠iℓj(1Γ(α)∫10(1−s)α−1(hi(s)+ϕi(s))ds)−(1−τ2)k∑j=1,j≠iℓj(1Γ(α)∫10(1−s)α−1(hj(s)+ϕj(s))ds). | (4.5) |
From (4.5), we deduce that
\begin{align*} \left| {{z_i}(\tau) - {\theta_i}(\tau)} \right| &\le \frac{2}{{\Gamma (\alpha + 3)}}{\varepsilon _i} + \frac{1}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1}^k {{\ell _j}} {\varepsilon _j} + \frac{1}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} {\varepsilon _i} + \frac{1}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} {\varepsilon _j}\\& \le \Big( {\frac{2}{{\Gamma (\alpha + 3)}} + \frac{2}{{\Gamma (\alpha + 1)}}} \Big){\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}},\;i = 1,2,\cdots, k. \end{align*} |
Similarly, applying the operator {}^C\mathfrak{D}_{0, \tau}^\beta on (4.5), we have
\begin{align*} {}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) \le& \frac{1}{{\Gamma (\alpha-\beta + 2)}}\int_0^\tau {{{(\tau - s)}^{\alpha-\beta + 1}}({h_i}(s) + {\phi _i}(s))ds}+\frac{{{\lambda _i}\rho _i^2}}{{\Gamma (2 - \beta )}}\int_0^\tau {{{(\tau - s)}^{1 - \beta }}{z_i}(s)ds} \\ &+ \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (3 - \beta )}}\sum\limits_{j = 1}^k {{\ell _j}} {\lambda _j}\rho _j^2{z_j}(1) + \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (\alpha )\Gamma (3 - \beta )}}\sum\limits_{j = 1}^k {{\ell _j}} \int_0^1 {{{(1 - s)}^{\alpha - 1}}} ({h_j}(s) + {\phi _j}(s))ds\\ &+ \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (3 - \beta )}}{\lambda _i}\rho _i^2{z_i}(1) + \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (\alpha )\Gamma (3 - \beta )}}{\ell _i}\int_0^1 {{{(1 - s)}^{\alpha - 1}}} ({h_i}(s) + {\phi _i}(s))ds\\ &+ \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (\alpha )\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} \int_0^1 {{{(1 - s)}^{\alpha - 1}}({h_j}(s) + {\phi _j}(s))} ds \\ &+ \frac{{2{\tau^{2 - \beta }}}}{{\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} {\lambda _j}\rho _j^2{z_j}(1),\;i = 1,2,\cdots,k. \end{align*} |
Then we have
\begin{align*} &\big|{{}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) - {}^C\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau)} \big|\\ \le& \frac{1}{{\Gamma (\alpha - \beta + 3)}}{\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1}^k {{\ell _j}} {\varepsilon _j} + \frac{2}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} {\varepsilon _j} + \frac{2}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}{\ell _i}{\varepsilon _i}\\ \le& \Big( {\frac{1}{{\Gamma (\alpha - \beta + 3)}} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big){\varepsilon _i} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} ,\;i = 1,2,\cdots,k. \end{align*} |
The proof is completed.
Lemma 4.2. If z = ({z_1}, {z_2}, \cdots, {z_k}) \in X is the solution of inequality (4.2). then, the following inequalities hold:
\begin{align*} \left| {{z_i}(\tau) - {\theta_i}(\tau)} \right| \le \Big( {\frac{{2{\Phi_i}(\tau)}}{{\Gamma (\alpha + 3)}} + \frac{{2{\Phi_j}(1)}}{{\Gamma (\alpha + 1)}}} \Big){\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} {\Phi_j}(1),\;i = 1,2, \cdots, k \end{align*} |
and
\begin{align*} \big| {{}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) - {}^C\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau)} \big| \le& \Big( {\frac{{{\Phi_i}(\tau)}}{{\Gamma (\alpha - \beta + 3)}} + \frac{{4{\Phi_j}(1)}}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big){\varepsilon _i}\\ &+ \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\Phi_j}{\varphi _j}(1)},\;i = 1,2, \cdots, k. \end{align*} |
Proof. The proof can be obtained using a similar analysis as in Lemma 4.1 and the fact that {\Phi _i}(\tau) \; i = 1, 2, \cdots, k are nondecreasing functions. Therefore, the proof is omitted.
Theorem 4.1. Suppose that (H_1) , (H_3) , and (3.9) hold. If \left| \lambda \right| < 1 , for every \lambda \in \mathbb{C} with \det(\lambda I-\mathcal{A}) = 0 , then system (2.1) is Ulam-Hyers stable, where
\begin{align*} \mathcal{A } = \left( {\begin{array}{*{20}{c}} {{Q_1}{\sigma _1} + {\pi _1}}&{{Q_2}{\sigma _2} + {\pi _2}}& \cdots &{{Q_2}{\sigma _k} + {\pi _k}}\\ {{Q_2}{\sigma _1} + {\pi _1}}&{{Q_1}{\sigma _2} + {\pi _2}}& \cdots &{{Q_2}{\sigma _k} + {\pi _k}}\\ \vdots & \vdots & \ddots & \vdots \\ {{Q_2}{\sigma _1} + {\pi _1}}&{{Q_2}{\sigma _2} + {\pi _2}}& \cdots &{{Q_1}{\sigma _k} + {\pi _k}} \end{array}} \right) \end{align*} |
and
{\sigma _i} = (\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}, \;{\pi _i} = \Big(3{\lambda _i}\rho _i^2 + \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}\Big). |
Proof. Let z = ({z_1}, {z_2}, \cdots, {z_k})\in X be the solution of inequality (4.1) and \bar z = ({\bar z_1}, {\bar z_2}, \cdots, {\bar z_k}) \in X be the solution of the following BVP:
\begin{align*} \left\{ \begin{array}{l} {}^C\mathfrak{D}_{0,\tau}^\alpha ({\mathcal{D}^2} + {\lambda _i}\rho _i^2){{\bar z}_i}(\tau) = \rho _i^{\alpha + 2}{f_i}\big(\tau,{{\bar z}_i}(\tau),\rho _i^{-\beta }{}^C\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)\big),\;i = 1,2, \cdots k,\\ {\bar z'_i}(0) = {{\bar z}_i}(1) = 0,\;\sum\nolimits_{i = 1}^k {\rho_i^{ - 2}{z''_i}(1) = 0,\;i = 1,2, \cdots k},\\ {\bar z''_i}(1) = {\bar z''_j}(1),\;i,j = 1,2, \cdots k,\;i \ne j.\\ \end{array} \right. \end{align*} | (4.6) |
According to Lemma 2.6 and Theorem 3.1, the solution to Eq (4.6) can be expressed as
\begin{align*} {{\bar z}_i}(\tau) = & \frac{{\rho _i^{\alpha + 2}}}{{\Gamma (\alpha + 2)}}\int_0^\tau {{{(\tau - s)}^{\alpha + 1}}{f_i}\big(s,{{\bar z}_i}(s),\rho _i^{ - \beta }{}^C\mathfrak{D}_{0,s}^\beta {{\bar z}_i}(s)\big)ds} \\ &- \frac{{\rho _i^{\alpha + 2}}}{{\Gamma (\alpha + 2)}}\int_0^1 {{{(1 - s)}^{\alpha + 1}}{f_i}\big(s,{{\bar z}_i}(s),\rho _i^{ - \beta }{}^C\mathfrak{D}_{0,s}^\beta {{\bar z}_i}(s)\big)ds} \\ &+ {\lambda _i}\rho _i^2{\int_0^1 {(1 - s){{\bar z}_i}(s)ds - {\lambda _i}\rho _i^2\int_0^t {(\tau - s){{\bar z}_i}(s)ds}}} \\ &+ (1 - {\tau^2})\sum\limits_{j = 1}^k {{\ell _j}\Big( {\frac{{\rho _j^{\alpha + 2}}}{{\Gamma (\alpha )}}\int_0^1 {{{(1 - s)}^{\alpha - 1}}} {f_j}\big(s,{{\bar z}_j}(s),\rho _j^{ - \beta }{}^C\mathfrak{D}_{0,s}^\beta {{\bar z}_j}(s)\big)ds - {\lambda _j}\rho _j^2{{\bar z}_j}(1)} \Big)} \\ &+ (1 - {\tau^2})\sum\limits_{j = 1,j \ne i}^k {{\ell _j}} \big( {{\lambda _j}\rho _j^2{{\bar z}_j}(1) - {\lambda _i}\rho _i^2{{\bar z}_i}(1)} \big)\\ &+ (1 - {\tau^2})\sum\limits_{j = 1,j \ne i}^k {\frac{{{\ell _j}\rho _i^{\alpha + 2}}}{{\Gamma (\alpha )}}} \int_0^1 {{{(1 - s)}^{\alpha - 1}}{f_i}\big(s,{{\bar z}_i}(s),\rho _i^{ - \beta }{}^CD_{0,s}^\beta {{\bar z}_i}(s)\big)} ds\\ &- (1 - {\tau^2})\sum\limits_{j = 1,j \ne i}^k {\frac{{{\ell _j}\rho _j^{\alpha + 2}}}{{\Gamma (\alpha )}}} \int_0^1 {{{(1 - s)}^{\alpha - 1}}} {f_j}\big(s,{{\bar z}_j}(s),\rho _j^{ - \beta }{}^CD_{0,s}^\beta {{\bar z}_j}(s)\big)ds,\;i = 1,2, \cdots k. \end{align*} |
Now, by Lemma 4.1, for \tau \in [0, 1] , we have
\begin{align*} \left| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right| \le& \left| {{z_i}(\tau) - {\theta_i}(\tau)} \right| + \left| {{\theta_i}(\tau) - {{\bar z}_i}(\tau)} \right|\\ \le& \Big( {\frac{2}{{\Gamma (\alpha + 3)}} + \frac{2}{{\Gamma (\alpha + 1)}}} \Big){\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} \\ &+ \Big( {\frac{2}{{\Gamma (\alpha + 3)}} + \frac{2}{{\Gamma (\alpha + 1)}}} \Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ 3{\lambda _i}\rho _i^2{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + 2\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} \\ & + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + \rho _j^{\alpha - \beta + 2}){W_j}{{\left\| {{z_i} - {{\bar z}_j}} \right\|}_X}} \end{align*} | (4.7) |
and
\begin{align*} &\big| {{}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) - {}^C\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)} \big| \le \big|{{}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) - {}^C\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau)} \big| + \big| {{}^C\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau) - {}^C\mathfrak{D}_{0,t\tau}^\beta {{\bar z}_i}(\tau)} \big|\\ \le& \Big( {\frac{1}{{\Gamma (\alpha - \beta + 3)}} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big){\varepsilon _i} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} \\ &+ \Big( {\frac{1}{{\Gamma (\alpha - \beta + 3)}} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \frac{4}{{\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2} {\left\| {{z_j} - {{\bar z}_j}} \right\|_X}\\ &+ \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + } \rho _j^{\alpha - \beta + 2}){W_j}{\left\| {{z_j} - {{\bar z}_j}} \right\|_X}. \end{align*} | (4.8) |
Therefore, from (4.7) and (4.8), it follows that
\begin{align*} &{\left\| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right\|_X} = \big\| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \big\| + \big\| {{}^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau) - {}^C\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)} \big\|\\ \le& {Q_1}{\varepsilon _i} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j} + } {Q_1}(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \Big( {3{\lambda _i}\rho _i^2 + \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}} \Big){\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ \sum\limits_{j = 1,j \ne i}^k {\Big( {2{\lambda _j}\rho _j^2 + \frac{{4{\lambda _j}\rho _j^2}}{{\Gamma (3 - \beta )}}} \Big){{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + \rho _j^{\alpha - \beta + 2}){W_j}{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} \\ \le&{Q_1}{\varepsilon _i} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j} + } {Q_1}(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \Big( {3{\lambda _i}\rho _i^2 + \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}} \Big){\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ \sum\limits_{j = 1,j \ne i}^k {\Big( {3{\lambda _j}\rho _j^2 + \frac{{5{\lambda _j}\rho _j^2}}{{\Gamma (3 - \beta )}}} \Big){{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + \rho _j^{\alpha - \beta + 2}){W_j}{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}}\\ \le& {Q_1}{\varepsilon _i} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j} + } {Q_1}{\sigma _i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + {\pi _i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \sum\limits_{j = 1,j \ne i}^k {{\pi _j}{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} \\ &+ {Q_2}\sum\limits_{j = 1,j \ne i}^k {{\sigma _j}{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}}. \end{align*} | (4.9) |
Meanwhile, inequality (4.9) can also have the form
\begin{align*} &{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},{{\left\| {{z_2} - {{\bar z}_2}} \right\|}_X}, \cdots ,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T}\\ &\le \mathcal{B}{({\varepsilon _1},{\varepsilon _2}, \cdots ,{\varepsilon _k})^T} + \mathcal{A}{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},\cdots,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T}, \end{align*} |
where
\begin{align*} \mathcal{B} = {({b_{ij}})_{k \times k}},\;{b_{ij}} = \left\{ \begin{array}{l} {Q_1},\;i = j,\\ {Q_2},\;i \ne j. \end{array} \right. \end{align*} |
Using matrix \mathcal{A} and Theorem 2.1, we get
\begin{align*} &{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},{{\left\| {{z_2} - {{\bar z}_2}} \right\|}_X}, \cdots ,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T}\\ &\le {(I - \mathcal{A})^{ - 1}}\mathcal{B}{({\varepsilon _1},{\varepsilon _2}, \cdots ,{\varepsilon _k})^T}, \end{align*} | (4.10) |
set
\begin{align*} C = {(I - \mathcal{A})^{ - 1}}\mathcal{B} = \left( {\begin{array}{*{20}{c}} {{c_{11}}}&{{c_{12}}}& \cdots &{{c_{1k}}}\\ {{c_{21}}}&{{c_{21}}}& \cdots &{{c_{2k}}}\\ \vdots & \vdots & \ddots & \vdots \\ {{c_{k1}}}&{{c_{k2}}}& \cdots &{{c_{kk}}} \end{array}} \right). \end{align*} |
Obviously, {c_{ij}} \ge 0 . Choose \varepsilon = \max \{ {\varepsilon _1}, {\varepsilon _2}, \cdots, {\varepsilon _k}\} . Then it follows from (4.10) that
\begin{align*} {\left\| {z - \bar z} \right\|_X} \le \Big( {\sum\limits_{i = 1}^k {\sum\limits_{i = 1}^k {{c_{ij}}} } } \Big)\varepsilon = {\Xi _\varepsilon }. \end{align*} | (4.11) |
Thus, system (2.1) is Ulam-Hyers stable.
Remark 4.2. Take {\Upsilon_{{f_1}, {f_2}, \cdots, {f_k}}}(\varepsilon) = {\Xi _\varepsilon } in (4.11). Obviously, we have {\Upsilon_{{f_1}, {f_2}, \cdots, {f_k}}}(0) = 0 . Then, using Definition 4.2, we conclude that system (2.1) is generalized Ulam-Hyers stable.
Theorem 4.2. Suppose that (H_1) , (H_3) , and (3.9) hold. Let {\Phi_i}(\tau) \in C([0, 1], {\mathbb{R}^+}) \; (i = 1, 2, \cdots, k) be nondecreasing. If \left| \lambda \right| < 1 , for every \lambda \in \mathbb{C} with \det(\lambda I-\mathcal{A}) = 0 , where \mathcal{A} is defined as before and the function \Phi is defined by
\Phi = \Phi({\Phi_1},{\Phi_2}, \cdots ,{\Phi_k}) \in C([0,1],{\mathbb{R}^ + }),\Phi(\tau) = \max \left\{ {{g_i}(\tau),i = 1,2, \cdots ,k} \right\} |
and
{g_i}(\tau) = \Big( {\frac{{{\Phi_i}(\tau)}}{{\Gamma (\alpha - \beta + 3)}} + \frac{{4{\Phi _j}(1)}}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}} + \frac{{2{\Phi_i}(\tau)}}{{\Gamma (\alpha + 3)}} + \frac{{2{\Phi_j}(\tau)}}{{\Gamma (\alpha + 1)}}} \Big), |
then system (2.1) is Ulam-Hyers-Rassias stable with respect to \Phi .
Proof. Assume that z = ({z_1}, {z_2}, \cdots, {z_k}) \in X is a solution of inequality (4.2). Also, let \bar z = ({\bar z_1}, {\bar z_2}, \cdots, {\bar z_k}) \in X be the unique solution of system (2.1). Then, combining Lemma 4.2 with an analysis similar to that used to prove Theorem 4.1, we obtain
\begin{align*} &\left| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right| \le \left| {{z_i}(\tau) - {\theta_i}(\tau)} \right| + \left| {{\theta_i}(\tau) - {{\bar z}_i}(\tau)} \right|\\ \le& \Big(\frac{{2{\Phi_i}(\tau)}}{{\Gamma (\alpha + 3)}} + \frac{{2{\Phi_j}(1)}}{{\Gamma (\alpha + 1)}}\Big){\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} {\Phi_j}(1)\\ &+ \Big(\frac{2}{{\Gamma (\alpha + 3)}} + \frac{2}{{\Gamma (\alpha + 1)}}\Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ 3{\lambda _i}\rho _i^2{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + 2\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} \\ &+ \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + \rho _j^{\alpha - \beta + 2}){W_j}{{\left\| {{z_i} - {{\bar z}_j}} \right\|}_X}},\;i = 1,2,\cdots,k \end{align*} | (4.12) |
and
\begin{align*} &{|^C}\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau){-^C}\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)| \le {|^C}\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau){-^C}\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau)| + {|^C}\mathfrak{D}_{0,\tau}^\beta {\theta_i}(\tau){ - ^C}\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)|\\ \le&\Big({\frac{{{\Phi_i}(\tau)}}{{\Gamma (\alpha - \beta + 3)}} + \frac{{4{\Phi_j}(1)}}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big){\varepsilon _i} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}{\Phi_j}(1)} \\ &+ \Big( {\frac{1}{{\Gamma (\alpha - \beta + 3)}} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \frac{4}{{\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2} {\left\| {{z_j} - {{\bar z}_j}} \right\|_X}\\ &+ \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + } \rho _j^{\alpha - \beta + 2}){W_j}{\left\| {{z_j} - {{\bar z}_j}} \right\|_X},\;i = 1,2, \cdots ,k. \end{align*} | (4.13) |
Hence, from (4.12) and (4.13), we get
\begin{align*} &\left\| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right\|\\ \le& \Big(\frac{{2{\Phi_i}(\tau)}}{{\Gamma (\alpha + 3)}} + \frac{{2{\Phi_j}(1)}}{{\Gamma (\alpha + 1)}}\Big){\varepsilon _i} + \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}} {\Phi_j}(1)\\ &+ \Big(\frac{2}{{\Gamma (\alpha + 3)}} + \frac{2}{{\Gamma (\alpha + 1)}}\Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ 3{\lambda _i}\rho _i^2{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + 2\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} \\ &+ \frac{2}{{\Gamma (\alpha + 1)}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + \rho _j^{\alpha - \beta + 2}){W_j}{{\left\| {{z_i} - {{\bar z}_j}} \right\|}_X}},\;i = 1,2,\cdots,k. \end{align*} | (4.14) |
Similarly, one can obtain
\begin{align*} &\big\| {^C\mathfrak{D}_{0,\tau}^\beta {z_i}(\tau){ - ^C}\mathfrak{D}_{0,\tau}^\beta {{\bar z}_i}(\tau)} \big\|\\ \le& \Big( {\frac{{{\Phi_i}(\tau)}}{{\Gamma (\alpha - \beta + 3)}} + \frac{{4{\Phi_j}(1)}}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big){\varepsilon _i} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\varepsilon _j}{\Phi_j}(1)} \\ &+ \Big( {\frac{1}{{\Gamma (\alpha - \beta +\underline{} 3)}} + \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}} \Big)(\rho _i^{\alpha + 2} + \rho _i^{\alpha - \beta + 2}){W_i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} \end{align*} |
\begin{align*} &+ \frac{{5{\lambda _i}\rho _i^2}}{{\Gamma (3 - \beta )}}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + \frac{4}{{\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {{\lambda _j}\rho _j^2} {\left\| {{z_j} - {{\bar z}_j}} \right\|_X}\\ &+ \frac{4}{{\Gamma (\alpha + 1)\Gamma (3 - \beta )}}\sum\limits_{j = 1,j \ne i}^k {(\rho _j^{\alpha + 2} + } \rho _j^{\alpha - \beta + 2}){W_j}{\left\| {{z_j} - {{\bar z}_j}} \right\|_X},\;i = 1,2, \cdots ,k. \end{align*} | (4.15) |
From (4.14) and (4.15), we find that
\begin{align*} &{\left\| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right\|_X} = \left\| {{z_i}(\tau) - {{\bar z}_i}(\tau)} \right\| + \big\| {^CD_{0,\tau}^\beta {z_i}(\tau){ - ^C}D_{0,\tau}^\beta {{\bar z}_i}(\tau)} \big\|\\ \le& {g_i}(\tau){\varepsilon _i} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {\varphi _j}(1){{\varepsilon _j} + } {Q_1}{\sigma _i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X} + {\pi _i}{\left\| {{z_i} - {{\bar z}_i}} \right\|_X}\\ &+ \sum\limits_{j = 1,j \ne i}^k {{\pi _j}{{\left\| {{z_j} - {{\bar z}_j}} \right\|}_X}} + {Q_2}\sum\limits_{j = 1,j \ne i}^k {{\sigma _j}{{\left\| {{z_j} -{{\bar z}_j}} \right\|}_X}}. \end{align*} | (4.16) |
We rewrite (4.16) as:
\begin{align*} &{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},{{\left\| {{z_2} - {{\bar z}_2}} \right\|}_X}, \cdots ,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T}\\ &\le \mathcal{B}(\tau){({\varepsilon _1},{\varepsilon _2}, \cdots ,{\varepsilon _k})^T} + \mathcal{A}{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},{{\left\| {{z_2} - {{\bar z}_2}} \right\|}_X}, \cdots ,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T}, \end{align*} |
where
\begin{align*} \mathcal{B} = {({b_{ij}})_{k \times k}},\;{b_{ij}} = \left\{ {\begin{array}{*{20}{l}} {{g_i}(\tau),\;i = j,}\\ {{Q_2},\;i \ne j.} \end{array}} \right. \end{align*} |
Using matrix \mathcal{A} and Theorem 2.1, we get
\begin{align} &{\left( {{{\left\| {{z_1} - {{\bar z}_1}} \right\|}_X},{{\left\| {{z_2} - {{\bar z}_2}} \right\|}_X}, \cdots ,{{\left\| {{z_k} - {{\bar z}_k}} \right\|}_X}} \right)^T} \le {(I - \mathcal{A})^{ - 1}}\mathcal{B}(\tau){({\varepsilon _1},{\varepsilon _2}, \cdots ,{\varepsilon _k})^T}, \end{align} | (4.17) |
and further, we define
\begin{align*} {(I - \mathcal{A})^{ - 1}} = \left( {\begin{array}{*{20}{c}} {{a_{11}}}&{{a_{12}}}& \cdots &{{a_{1k}}}\\ {{a_{21}}}&{{a_{22}}}& \cdots &{{a_{2k}}}\\ \vdots & \vdots & \ddots & \vdots \\ {{a_{k1}}}&{{a_{k2}}}& \cdots &{{a_{kk}}}, \end{array}} \right), C(\tau) = \left( {\begin{array}{*{20}{c}} {{c_{11}}(\tau)}&{{c_{12}}(\tau)}& \cdots &{{c_{1k}}(\tau)}\\ {{c_{21}}(\tau)}&{{c_{22}}(\tau)}& \cdots &{{c_{2k}}(\tau)}\\ \vdots & \vdots & \ddots & \vdots \\ {{c_{k1}}(\tau)}&{{c_{k2}}(\tau)}& \cdots &{{c_{kk}}(\tau)} \end{array}} \right). \end{align*} |
It is easy to verify that
{a_{ij}} \ge 0,\;{c_{ij}}(\tau)\ge 0,\;i,j = 1,2, \cdots ,k |
and
\begin{align*} {c_{ij}}(\tau) & = {a_{ij}}{g_j}(\tau) + {Q_2}{\Phi_j}(1)\sum\limits_{r = 1,r \ne j}^k {{a_{ir}}} \le \Big( {{a_{ij}} + {Q_2}\frac{{{\Phi_j}(1)}}{{{g_j}(0)}}\sum\limits_{r = 1,r \ne j}^k {{a_{ir}}} } \Big){g_j}(\tau),\;i,j = 1,2, \cdots ,k. \end{align*} |
Setting \varepsilon = \max \{ {\varepsilon _1}, {\varepsilon _2}, \cdots, {\varepsilon _k}\} , we have
\begin{align*} {\left\| {z - \bar z} \right\|_X} \le \sum\limits_{j = 1}^k {\sum\limits_{i = 1}^k {\Big( {{a_{ij}} + { Q_2}\frac{{{\Phi_j}(1)}}{{{g_j}(0)}}\sum\limits_{r = 1,r \ne j}^k {{a_{ir}}} } \Big)} } \Phi (\tau)\varepsilon. \end{align*} | (4.18) |
Let
{c_{{f_1},{f_2}, \cdots ,{f_k},\Phi }} = \sum\limits_{j = 1}^k {\sum\limits_{i = 1}^k {\Big( {{a_{ij}} + {Q_2}{\Phi_j}(1){g^{ - 1}}_j(0)\sum\limits_{r = 1,r \ne j}^k {{a_{ir}}} } \Big)}}. |
By Definition 4.3, system (2.1) is Ulam-Hyers-Rassias stable with respect to \Phi .
Remark 4.3. Taking \varepsilon = 1 in (4.18), we conclude using Definition 4.4 that system (2.1) is generalized Ulam-Hyers-Rassias stable with respect to \Phi .
Example 5.1. Consider the BVP (1.4) with \alpha = \frac{1}{2}, \; \beta = \frac{1}{3}, \; k = 3, \; {\lambda _1} = \frac{1}{2}, \; {\lambda _2} = \frac{1}{4}, \; {\lambda _3} = \frac{1}{8}, \; {\rho _1} = {\rho _2} = \frac{1}{{10}} , {\rho _3} = \frac{1}{5} , and
\begin{align*} \left\{ {\begin{array}{*{20}{l}} {{f_1}(t,u,v) = \frac{t}{5} + \frac{u}{{4{{(t + 3)}^2}}} + \frac{5}{{3\sqrt 2 (t + 2)}}v,\;(t,u,v) \in [0,{\rho _1}] \times \mathbb{R} \times \mathbb{R},}\\ {{f_2}(t,u,v) = \frac{\cos x}{3}+ \frac{u}{{2{{(t + 4)}^3}}} + \frac{{5t}}{{6\sqrt 2 }}v,\;(t,u,v) \in [0,{\rho _2}] \times \mathbb{R} \times \mathbb{R},}\\ {{f_3}(t,u,v) = 2{t^2} + \frac{u}{{2{{(t + 5)}^2}}} + \frac{v}{{6(t + 2)}},\;(t,u,v) \in [0,{\rho _3}] \times \mathbb{R} \times \mathbb{R}.} \end{array}} \right. \end{align*} |
Using Lemma 2.5, we obtain the equivalent system
\begin{align*} \left\{ \begin{array}{l} {}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big({\mathcal{D}^2} + \frac{1}{{200}}\big){z_1}(\tau) = {\big(\frac{1}{2}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big({\frac{\tau }{5} + \frac{{{z_1}(\tau )}}{{4{{(\tau + 3)}^2}}} +{{\big(\frac{1}{2}\big)}^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{5}{{3\sqrt 2 (\tau + 2)}}{}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_1}(\tau )} \Big),\\ \\ {}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big({\mathcal{D}^2} + \frac{1}{{400}}\big){z_2}(\tau ) = {\big(\frac{1}{4}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big( {\frac{{\cos \tau }}{3} + \frac{{{z_2}(\tau )}}{{2{{(\tau + 4)}^3}}}+{{(\frac{1}{4})}^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{5}{{6\sqrt 2 }}{}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_2}(\tau )} \Big),\\ \\ {}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big({\mathcal{D}^2} + \frac{1}{{200}}\big){z_3}(\tau ) = {\big(\frac{1}{8}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big( {2{\tau ^2} + \frac{{{z_3}(\tau )}}{{2{{(\tau + 5)}^2}}}+{{\big(\frac{1}{8}\big)}^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{1}{{6(\tau + 2)}}{}^CD_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_3}(\tau )} \Big),\\ {{z'_1}}(0) = {{z'_2}}(0) = {{z'_3}}(0) = {z_1}(0) = {z_2}(0) = {z_3}(0) = 0,\\ {{z''_1}}(1) = {{z''_2}}(1) = {{z''_3}}(1),\;9{{z''_1}}(1) + 16{{z''_2}}(1) + 25{{z''_3}}(1) = 0, \end{array} \right. \end{align*} | (5.1) |
then
\begin{gather*} {\xi _1}(\tau ) = \frac{\tau }{5},\;{\xi _2}(\tau ) = \frac{{\cos \tau }}{3},\;{\xi _3}(\tau ) = 2{\tau ^2},\\ {\eta _1}(\tau ) = \frac{1}{{4{{(\tau + 3)}^2}}},\;{\eta _2}(\tau ) = \frac{1}{{2{{(\tau + 4)}^3}}},\;{\eta _3}(\tau ) = \frac{1}{{2{{(\tau + 5)}^2}}},\\ {\psi _1}(\tau ) = {\big(\frac{1}{2}\big)^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{5}{{3\sqrt 2 {(\tau + 2)}}},\;{\psi _2}(\tau ) = {\big(\frac{1}{4}\big)^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{5}{{6\sqrt 2 }},\;\;{\psi _3}(\tau ) = {\big(\frac{1}{{8}}\big)^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\frac{1}{{6(\tau + 2)}}. \end{gather*} |
For \tau\in[0, 1] , we have \xi_1^ * = \frac{1}{5}, \; \xi _2^ * = \frac{1}{3}, \; \xi _3^ * = 2, \; \eta _1^ * = \frac{1}{{36}}, \; \eta _2^ * = \frac{1}{{128}}, \; \eta _3^ * = \frac{1}{{50}}, \; \psi _1^ * = \psi _2^ * = \frac{5}{{3}}, \; \psi _3^ * = \frac{1}{{4}} . By calculation, we get
\begin{align*} &{L_1} = 0.06674,\;{\Delta _1} = 0.022,\;{\tilde \Delta _1} = 0.01664,\;{\Omega _1} = 0.0317,\;{\tilde \Omega _1} = 0.01168,\;{N_1} = 0.1982,\;\\ &{L_2} = 0.06257,\;{\Delta _2} = 0.022,\;{\tilde \Delta _2} = 0.01664,\;{\Omega _2} = 0.01586,\;{\tilde \Omega _2} = 0.01168,\;{N_2} = 0.1988,\\ &{L_3} = 0.07842,\;{\Delta _3} = 0.1242,\;{\tilde \Delta _3} = 0.09410,\;{\Omega _3} = 0.0317,\;{\tilde \Omega _3} = 0.0234,\;{N_3} = 0.2573, \end{align*} |
so, we have
\begin{align*} {\theta _1} = {\Delta _1}(\eta _1^* + \rho _1^{ - \beta }\psi _1^*) + {\Omega _1} + {\tilde \Delta _2}(\eta _2^* + \rho _2^{ - \beta }\psi _2^*) + {\tilde \Omega _2} + {\tilde \Delta _3}(\eta _3^* + \rho _3^{ - \beta }\psi _3^*) + {\tilde \Omega _3} = 0.2487,\\ {\theta _2} = {\Delta _2}(\eta _2^* + \rho _2^{ - \beta }\psi _2^*) + {\Omega _2} + {{\tilde \Delta }_1}(\eta _1^* + \rho _1^{ - \beta }\psi _1^*) + {{\tilde \Omega }_1} + {{\tilde \Delta }_3}(\eta _3^* + \rho _3^{ - \beta }\psi _3^*) + {{\tilde \Omega }_3} = 0.2445,\\ {\theta _3} = {\Delta _3}(\eta _3^* + \rho _3^{ - \beta }\psi _3^*) + {\Omega _3} + {\tilde \Delta _1}(\eta _1^* + \rho _1^{ - \beta }\psi _1^*) + {\tilde \Omega _1} + {\tilde \Delta _2}(\eta _2^* + \rho _2^{ - \beta }\psi _2^*) + {\tilde \Omega _2} = 0.2448, \end{align*} |
and
\begin{align*} \sum\limits_{i = 1}^3 {{\theta _i}} = 0.736 < 1,\;\sum\limits_{i = 1}^3 {{N_i}} = 0.6543. \end{align*} |
Thus,
r > \frac{{\sum\nolimits_{i = 1}^3 {{N_i}} }}{{1 - \sum\nolimits_{i = 1}^3 {{\theta _i}} }} = \frac{{0.6543}}{{1 - 0.736}} \buildrel .\over = 2.479. |
According to Theorem 3.1, BVP (5.1) has at least one solution on [0, 1].
Example 5.2. Consider the BVP (1.4) with \alpha = \frac{1}{2}, \; \beta = \frac{1}{3}, \; k = 3, \; \lambda_1 = \lambda_2 = \lambda_3 = \frac{1}{10}, \; \rho_1 = \rho_2 = \rho_3 = \frac{1}{5} , and
\begin{align*} \left\{ \begin{array}{l} {f_1}(t,u,v) = \cos t + \frac{1}{{3{{(\sqrt t + 3)}^2}}}(\sin u + v),\;(t,u,v) \in [0,{\rho _1}] \times \mathbb{R} \times \mathbb{R},\\ {f_2}(t,u,v) = \frac{1}{t} + \frac{{\sqrt \pi }}{{(t + 27)}}(\left| u \right| + \left| v \right|),\;(t,u,v) \in [0,{\rho _2}] \times \mathbb{R} \times \mathbb{R},\\ {f_3}(t,u,v) = 1 + 2{t^2} + \frac{{2\sqrt 2 }}{{9(t + 3)}}(\frac{u}{{1 + u}} + v),\;(t,u,v) \in [0,{\rho _3}] \times \mathbb{R} \times \mathbb{R}. \end{array} \right. \end{align*} |
Using Lemma 2.5, we obtain the equivalent system
\begin{align*} \left\{ \begin{array}{l} {}^C\mathfrak{D}_{0,\tau }^{{1\mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big({\mathcal{D}^2} + \frac{1}{{250}}\big){z_1}(\tau ) = {\big(\frac{1}{5}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big[ {\cos \tau + \frac{1}{{3{{(\sqrt \tau + 3)}^2}}}\big( {\sin {z_1}(\tau ) + {\big(\frac{1}{5}\big)^{{{-1} \mathord{\left/ {\vphantom {{-1} 3}} \right. } 3}}}{}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_1}(\tau )} \big)}\Big],\\ \\ {}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big(\mathcal{D}^2 + \frac{1}{{250}}\big){z_2}(\tau) = {\big(\frac{1}{5}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big[{\frac{1}{\tau } + \frac{{\sqrt \pi }}{{(\tau + 27)}}\big( {\left| {{z_2}(\tau )}\right|+ {{\big(\frac{1}{5}\big)}^{{{-1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}\big|{{}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_2}(\tau)}\big|} \big)} \Big],\\ \\ {}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}\big(\mathcal{D}^2 + \frac{1}{{250}}\big){z_3}(\tau ) = {\big(\frac{1}{5}\big)^{{5 \mathord{\left/ {\vphantom {5 2}} \right. } 2}}}\Big[ {1 + 2{\tau ^2} + \frac{{2\sqrt 2 }}{{9(\tau + 3)}}\big( {\frac{\tau }{{1 + \tau }} + {{\big(\frac{1}{5}\big)}^{{{ - 1} \mathord{\left/ {\vphantom {{ - 1} 3}} \right. } 3}}}{}^C\mathfrak{D}_{0,\tau }^{{1 \mathord{\left/ {\vphantom {1 3}} \right. } 3}}{z_3}(\tau)} \big)} \Big],\\ {{z'_1}}(0) = {{z'_2}}(0) = {{z'_3}}(0) = {z_1}(0) = {z_2}(0) = {z_3}(0) = 0,\\ {{z''_1}}(1) = {{z''_2}}(1) = {{z''_3}}(1),\;9{{z''_1}}(1) + 16{{z''_2}}(1) + 25{{z''_3}}(1) = 0, \end{array} \right. \end{align*} | (5.2) |
and for \tau\in[0, 1] , u, v, u_1, v_1\in \mathbb{R} , we can conclude that
\begin{align*} &\big|{{f_1}(\tau,u,v) - {f_1}(\tau ,{u_1},{v_1})} \big| \le \frac{1}{{3{{(\sqrt \tau + 3)}^2}}}\big(\big|{u - v} \big|+\big|{{u_1}-{v_1}}\big|\big),\\ &\big|{{f_2}(\tau, u, v) - {f_2}(\tau,{u_1},{v_1})} \big| \le \frac{{\sqrt \pi }}{{(\tau + 27)}}\big(\big|{u - v} \big| + \big|{{u_1}-{v_1}}\big|\big),\\ &\big|{{f_3}(\tau, u, v)- {f_3}(\tau ,{u_1},{v_1})} \big| \le \frac{{2\sqrt 2 }}{{9(\tau + 3)}}\big(\big|{u - v} \big| +\big| {{u_1}-{v_1}}\big|\big), \end{align*} |
and so, we get
{w_1}(\tau ) = \frac{1}{{3{{(\sqrt \tau + 3)}^2}}},\;{w_2}(\tau ) = \frac{{\sqrt \pi }}{{(\tau + 27)}},\;{w_3}(\tau ) = \frac{{2\sqrt 2 }}{{9(\tau + 3)}}. |
By simple calculation, we obtain
\begin{gather*} a = {Q_1}{\sigma _i} + {\pi _i} = 0.1652,\;b = {Q_2}{\sigma _i} + {\pi _i} = 0.1316,\;i = 1,2,3,\\ {W_1} = {W_2} = {W_3} = \mathop {\max }\limits_{\tau \in [0,1]} \left| {{w_1}(\tau )} \right| = \frac{1}{{27}},\;{\sigma _1} = {\sigma _2} = {\sigma _3} = 0.0202,\\ {K_1} = {K_2} = {K_3}\buildrel .\over = 0.8467,\;{L_1} = {L_2} = {L_3}\buildrel .\over = 0.04396,\;{\pi _1} = {\pi _2} = {\pi _3} = 0.02531. \end{gather*} |
Then
\begin{align*} \Big(\sum\limits_{i = 1}^k {{K_i}\Big)\Big(\sum\limits_{i = 1}^k {{W_i}}}\Big)+\sum\limits_{i = 1}^k {{L_i}}\doteq 0.4450 < 1. \end{align*} |
Since all conditions of Theorem 3.2 have been satisfied, therefore, the system (5.2) has a unique solution in [0, 1]. Using the given value, we also have
\begin{align*} \mathcal{A } = \left( {\begin{array}{*{20}{c}} {0.1652}&{0.1316}&{0.1316}\\ {0.1316}&{0.1652}&{0.1316}\\ {0.1316}&{0.1316}&{0.1652} \end{array}} \right). \end{align*} |
Let
\begin{align*} 0 = \det (\lambda E - \mathcal{A}) = (\lambda - 0.4288){(\lambda - 0.034)^2}. \end{align*} | (5.3) |
Solving Eq (5.3) gives
{\lambda _1} = 0.4288 < 1,\;{\lambda _2} = {\lambda _3} = 0.034 < 1. |
From Theorem 4.1 and Remark 4.2, it can be seen that the system (5.2) is Ulam-Hyers stable and generalized Ulam-Hyers stable. Similarly, we obtain that system (5.2) is Ulam-Hyers-Rassia stable and generalized Ulam-Hyers-Rassia stable.
This article discussed a class of nonlinear Caputo type higher-order fractional Langevin equations on a star graph. By utilizing Lemmas 2.4 and 2.5, BVP (1.4) was transformed into system (2.1) defined on the interval [0, 1]. The existence and uniqueness of solutions are proven using fixed point theorems, specifically the Krasnoselskii fixed point theorem and the Banach contraction mapping principle. Furthermore, the Ulam-Hyers stability, Ulam-Hyers-Rassias stability, and their generalized forms are explored based on Definitions 4.1–4.4, which may provide researchers with a new approach to analyzing the Ulam stability of higher-order fractional differential equations. The results presented in this article are new and extend some existing literature on this topic (see prior references[10,11,15,17,23]). Finally, two examples demonstrated the application of the main results. One promising avenue for future research is to explore fractional differential equations on star graphs, including the fractional Sturm-Liouville equation, the fractional Langevin equation with the p -Laplacian operator, and fractional integral-differential equations.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
This research is supported by the National Natural Science Foundation of China (11601007) and the Graduate Innovation Fund of Anhui University of Science and Technology (2023cx2146).
The authors declare that they have no competing interests.
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