In this paper, we proposed and studied a simple five-dimensional mathematical model that describes the second and third stages of the anaerobic degradation process under the influence of leachate recirculation. The state variables are the concentration of insoluble substrate, soluble substrate, produced hydrogen, acetogenic bacteria and hydrogenotrophic-methanogenic bacteria. The growth rates of used bacteria will be of general nonlinear form. The stability of the steady states will be studied by reducing the model to a 3D system. According to the operating parameters of the bioreactor described by the added insoluble substrate, soluble substrate and hydrogen input concentrations and the dilution rate, we proved that the model can admit multiple equilibrium points and we gave the necessary and sufficient assumptions for their existence, their uniqueness and their stability. In particular, the uniform persistence of the system was satisfied under some natural assumptions on the growth rates. Then, a question was answered related to the management of renewable resources where the goal of was to propose an optimal strategy of leachate recirculation to reduce the organic matter (either soluble or insoluble) and keep a limitation of the costs of the recirculation operation during the process. The findings of this work were validated by an intensive numerical investigation.
Citation: Miled El Hajji. Mathematical modeling for anaerobic digestion under the influence of leachate recirculation[J]. AIMS Mathematics, 2023, 8(12): 30287-30312. doi: 10.3934/math.20231547
[1] | Ying Sun, Yuelin Gao . An improved composite particle swarm optimization algorithm for solving constrained optimization problems and its engineering applications. AIMS Mathematics, 2024, 9(4): 7917-7944. doi: 10.3934/math.2024385 |
[2] | Juhe Sun, Guolin Huang, Li Wang, Chuanjun Yin, Ning Ma . A multi-strategy upgraded Harris Hawk optimization algorithm for solving nonlinear inequality constrained optimization problems. AIMS Mathematics, 2025, 10(5): 11783-11812. doi: 10.3934/math.2025533 |
[3] | Bothina El-Sobky, Yousria Abo-Elnaga, Gehan Ashry . A nonmonotone trust region technique with active-set and interior-point methods to solve nonlinearly constrained optimization problems. AIMS Mathematics, 2025, 10(2): 2509-2540. doi: 10.3934/math.2025117 |
[4] | Aziz Belmiloudi . Time-varying delays in electrophysiological wave propagation along cardiac tissue and minimax control problems associated with uncertain bidomain type models. AIMS Mathematics, 2019, 4(3): 928-983. doi: 10.3934/math.2019.3.928 |
[5] | Yu Yuan, Qicai Li . Maximizing the goal-reaching probability before drawdown with borrowing constraint. AIMS Mathematics, 2021, 6(8): 8868-8882. doi: 10.3934/math.2021514 |
[6] | Yunjae Nam, Dongsun Lee . Efficient one asset replacement scheme for an optimized portfolio. AIMS Mathematics, 2022, 7(9): 15881-15903. doi: 10.3934/math.2022869 |
[7] | Jun Moon . A Pontryagin maximum principle for terminal state-constrained optimal control problems of Volterra integral equations with singular kernels. AIMS Mathematics, 2023, 8(10): 22924-22943. doi: 10.3934/math.20231166 |
[8] | Hengdi Wang, Jiakang Du, Honglei Su, Hongchun Sun . A linearly convergent self-adaptive gradient projection algorithm for sparse signal reconstruction in compressive sensing. AIMS Mathematics, 2023, 8(6): 14726-14746. doi: 10.3934/math.2023753 |
[9] | Zahra Pirouzeh, Mohammad Hadi Noori Skandari, Kamele Nassiri Pirbazari, Stanford Shateyi . A pseudo-spectral approach for optimal control problems of variable-order fractional integro-differential equations. AIMS Mathematics, 2024, 9(9): 23692-23710. doi: 10.3934/math.20241151 |
[10] | Regina S. Burachik, Bethany I. Caldwell, C. Yalçın Kaya . Douglas–Rachford algorithm for control- and state-constrained optimal control problems. AIMS Mathematics, 2024, 9(6): 13874-13893. doi: 10.3934/math.2024675 |
In this paper, we proposed and studied a simple five-dimensional mathematical model that describes the second and third stages of the anaerobic degradation process under the influence of leachate recirculation. The state variables are the concentration of insoluble substrate, soluble substrate, produced hydrogen, acetogenic bacteria and hydrogenotrophic-methanogenic bacteria. The growth rates of used bacteria will be of general nonlinear form. The stability of the steady states will be studied by reducing the model to a 3D system. According to the operating parameters of the bioreactor described by the added insoluble substrate, soluble substrate and hydrogen input concentrations and the dilution rate, we proved that the model can admit multiple equilibrium points and we gave the necessary and sufficient assumptions for their existence, their uniqueness and their stability. In particular, the uniform persistence of the system was satisfied under some natural assumptions on the growth rates. Then, a question was answered related to the management of renewable resources where the goal of was to propose an optimal strategy of leachate recirculation to reduce the organic matter (either soluble or insoluble) and keep a limitation of the costs of the recirculation operation during the process. The findings of this work were validated by an intensive numerical investigation.
Fractional calculus has been widely and deeply used in many fields, for example, continuum mechanics, control theory of dynamical systems, and so on. For this reason, fractional differential equations (FDEs, in short), as a useful tool to model the dynamics of numerous physical systems, have gained considerable popularity in physics, population dynamics, chemical technology, control of dynamical systems, etc. For further details on FDEs, see [1,2,3] and their references.
In the last few decades, as a significant branch of FDEs, impulsive differential equation (IDE, for short), which provides a natural description of observed evolution processes, has been emerging as a very meaningful research area. In addition, IDEs are also as important mathematical tools for better understanding real-world problems (see, for instance, [4,5,6,7,8]). Hence, many authors have used IDEs to describe some phenomenon with abrupt changes, such as, harvest, disease, control theory of dynamical systems and so on. For example, [9,10,11] researched some different types IDEs, which are nonlinear impulsive differential systems with infinite delays, impulsive neural networks, singularly perturbed nonlinear impulsive differential systems with delays of small parameter, respectively. Moreover, [12] studied persistence of delayed cooperative models by means of impulsive control method.
Meanwhile, boundary value problems (BVPs, for short) of IDEs have been researched extensively and deeply. Correspondingly, many scholars have studied some BVPs of fractional differential equations (FIDEs, for short) and obtain lots of important conclusions. For example, [13] researched singular semipositive BVPs of fourth-order differential systems with parameters. [14] studied a class of BVPs for nonlinear fractional Kirchhoff equations and obtained the existence of multiple sign-changing solutions.
As far as we know, continuity is a fundamental assumption in degree theory. However, there are a lot of discontinuous differential equations in many areas, such as, automatic control, neural network, etc. Because of the corresponding operators are not continuous, general topological degree theory is invalid to studying the existence of solutions for most discontinuous differential equations, such as, [20,21]. To overcome this problem, a new definition of topological degree for a class of discontinuous operators is introduced by R. Figueroa et al. Subsequently, a number of fixed point theorems for such operators are derived in [16], such as, Schauder-type and Krasnoselskii's theorem for discontinuous operators. Then they are used to solve discontinuous differential systems. For example, [17] considered the existence for a class of second-order discountious BVPs by constructing a closed-convex Krasovskij envelope and Schauder-type theorem for discontinuous operators. [18] researched a class of BVPs of second-order discontinuous differential equations with impulse effects by using the nonlinear alternative of Krasnoselskii's fixed point theorem for discontinuous operators on cones.
However, to our best knowledge, there are few studies on multiple solutions for integral boundary value problems of fractional discontinuous differential equations with impulse effects. The purpose of present paper is to fill this gap.
Motivated by the above discussions, this paper studies multiple solutions for the following boundary value problem:
{CtDR0+Λ(t)=E(t)F(t,Λ(t)), a.e. t∈Q′,△Λ|t=tκ=Φκ(Λ(tκ)), κ=1, 2, ⋯, m,△Λ′|t=ti=0, κ=1, 2, ⋯, m,ϑΛ(0)−χΛ(1)=∫10ϱ1(υ)Λ(υ)dυ,ζΛ′(0)−δΛ′(1)=∫10ϱ2(υ)Λ(υ)dυ, | (1.1) |
where CtDR0+ is the Caputo fractional derivative with t, 1<R<2, ϑ>χ>0, ζ>δ>0, Ek∈C( R +, R +), E, ϱ1, ϱ2≥0 a.e. on J=[0,1], Q′=Q∖{t1, ⋯, tm}, E, ϱ1, ϱ2∈L1(0,1), ϝ:Q× R +→ R +, R +=[0,+∞), 0<t1<t2<⋯<tm<1. △Λ|t=tk, △Λ′|t=tk denote the jump of Λ(t) and Λ′(t) at t=tk, respectively. This paper has the following innovations and features. Firstly, BVP (1.1) is of fractional discontinuous differential equations with instantaneous impulse effects. The nonlinearity F here is discontinuous over countable families of curve[22]. Secondly, the boundary value condition considered here is of integral type. It makes BVP (1.1) more widely applicable in solving practical problems. Thirdly, the used approach in this paper has certain advantages over some reference as above. In detail, the distinctive tool used here is multivalued analysis in the study of discontinuous problems and the novelty is the use of multivalued analysis to obtain results for single-valued operators. Compared with [18], we redefine the admissible continuous curves for the new system (1.1). At the same time, a suitable cone is established by researching properties of Green's function deeply. Therefore, the positive solutions can be obtained by means of Krasnoselskii's fixed point theorem for discontinuous operators on cones.
The rest of this paper is organized as follows. Some basic definitions and notations are contained in Section 2. Section 3 presents the main results. Finally, an illustrative example is given in Section 4.
In this section, we first introduce some definitions and lemmas that are used in this paper.
Definition 2.1. [3] The Riemann-Liouville fractional integral of order ℜ∈R+ of a function ϝ on interval (α,β) is defined as follows:
(Iℜ0+ϝ)(t)=1Γ(ℜ)∫tα(t−υ)R−1ϝ(υ)dυ. |
Definition 2.2. [3] The Caputo fractional derivative of order ℜ∈R+ of a function ϝ on interval (α,β) is defined as follows:
(CtDR0+)ϝ(t)=1Γ(n−R)∫tα(t−υ)n−R−1ϝ(n)(υ)dυ. |
Let
PC(Q)={Λ:[0,1]→R,Λ∈C(Q′), and Λ(t+κ), Λ(t−κ) exists,and Λ(t−κ)=Λ(tκ), 1≤κ≤m}, |
and
PC1(Q)={Λ:[0,1]→R,Λ∈PC(Q), CtDℜ−10+Λ∈PC(Q), CtDℜ−10+Λ(t+κ), CtDℜ−10+Λ′(t−κ)exists, and CtDℜ−10+Λ(t−κ)= CtDℜ−10+Λ(tκ), 1≤κ≤m}. |
Obviously, they are Banach spaces with the norm
‖Λ‖0=sup0≤t≤1|Λ(t)| |
and
‖Λ‖1=max{‖Λ‖0, ‖CtDℜ−10+Λ‖0}, |
respectively.
For the sake of simplicity, let Aj=∫10ϱj(υ)dυ, Qj=1ϑ−χAj (j=1,2) , Pj=∫10(ϑ−χ)υ+χ(ϑ−χ)(ζ−δ)ϱj(υ)dυ, Γ1=(1−P2)(1−Q1)−P1Q2 and QM=max{Q2Γ(ζ−δ),1−Q1Γ(ζ−δ)}.
Lemma 2.3. If (1−P2)(1−Q1)≠P1Q2, for H∈L(Q, R +), the following boundary value problem
{CtDℜ0+Λ(t)=H(t), a.e. t∈Q′,△Λ|t=tκ=Φκ(Λ(tκ)), κ=1, 2, ⋯, m,△Λ′|t=tκ=0, κ=1, 2, ⋯, m,ϑΛ(0)−χΛ(1)=∫10ϱ1(υ)Λ(υ)dυ,ζΛ′(0)−δΛ′(1)=∫10ϱ2(υ)Λ(υ)dυ, | (2.1) |
has a solution
Λ(t)=∫10H1(t,υ)H(υ)dυ+m∑i=1H2(t,ti)Φi(Λ(ti)), |
where
H1(t,υ)=ℵ(t,υ)+2∑n=1φn(t)∫10ℵ(υ,t)ϱn(t)dt, |
H2(t,ti)={χϑ−χ+χϑ−χ2∑n=1Anφn(t),0≤t≤ti≤1;ϑϑ−χ+ϑϑ−χ2∑n=1Anφn(t),0≤ti<t≤1, |
φ1(t)=(ζ−δ)(1−P2)+[χ+(ϑ−χ)t]Q2(ϑ−β)(ζ−δ)Γ1, |
φ2(t)=(ζ−δ)P1+[χ+(ϑ−χ)t](1−Q1)(ϑ−χ)(ζ−δ)Γ1. |
and
ℵ(t,υ)={χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+[χδ+(ϑ−χ)δt](1−υ)ℜ−2(ϑ−β)(ζ−δ)Γ(ℜ−1)+(t−υ)q−1Γ(ℜ),0≤υ≤t≤1;χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+[χδ+(ϑ−χ)δt](1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1),0≤t≤υ≤1. |
Proof. Let Λ be a general solution on each interval (tκ,tκ+1] (κ=0, 1, 2, ⋯, m). By integrating both sides of Eq (2.1), one can obtain that
Λ(t)=1Γ(ℜ)∫t0(t−υ)ℜ−1H(υ)dυ−cκ−dt, for t∈(tκ,tκ+1], | (2.2) |
where t0=0, tm+1=1. Then,
Λ′(t)=1Γ(ℜ−1)∫t0(t−υ)ℜ−2H(υ)dυ−d, t∈(tκ,tκ+1]. |
In view of Eq (2.1), we get
−ϑc0−χ[1Γ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ−cm−d]=∫10ϱ1(υ)Λ(υ)dυ, | (2.3) |
−ζd−δ[1Γ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ−d]=∫10ϱ2(υ)Λ(υ)dυ, | (2.4) |
cκ−1−cκ=Φκ(Λ(tκ)), | (2.5) |
and
d=−∫10ϱ2(υ)Λ(υ)dυ+δΓ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυζ−δ. | (2.6) |
From (2.3), (2.5) and (2.6), one can easily get that
c0 = −1ϑ−χ[∫10ϱ1(υ)Λ(υ)dυ+χΓ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ+χm∑i=1Φi(Λ(ti))+χ(∫10ϱ2(υ)Λ(υ)dυ+δΓ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ)ζ−δ], | (2.7) |
and
cκ = c0−κ∑i=1Φi(Λ(ti))= −1ϑ−χ[∫10ϱ1(υ)Λ(υ)dυ+χΓ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ+χm∑i=1Φi(Λ(ti))+χ(∫10ϱ2(υ)Λ(υ)dυ+δΓ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ)ζ−δ]−κ∑i=1Φi(Λ(ti)). | (2.8) |
Hence, (2.7) and (2.8) imply that
cκ+dt=−1ϑ−χ[∫10ϱ1(υ)Λ(υ)dυ+χΓ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ+χm∑i=1Φi(Λ(ti))+χ(∫10ϱ2(υ)Λ(υ)dυ+δΓ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ)ζ−δ]−κ∑i=1Φi(Λ(ti))+[−∫10ϱ2(υ)Λ(υ)dυ+δΓ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυζ−δ]t=−∫10ϱ1(υ)Λ(υ)dυϑ−χ−(ϑ−χ)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(s)Λ(υ)dυ−χ(ϑ−χ)Γ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ−δ[(ϑ−χ)t+χ](ϑ−χ)(ζ−δ)1Γ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ−χϑ−χm∑i=1Φi(Λ(ti))−κ∑i=1Φi(Λ(ti)), | (2.9) |
for κ=0, 1, 2, ⋯, m. Now substituting (2.9) into (2.2), for t∈Q0=[0,t1],
Λ(t)=1Γ(ℜ)∫t0(t−υ)ℜ−1H(υ)dυ+∫10ϱ1(υ)Λ(υ)dυϑ−χ+(ϑ−β)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(υ)Λ(υ)dυ+χ(ϑ−χ)Γ(ℜ)∫10(1−υ)ℜ−1H(υ)dυ+δ[(ϑ−χ)t+χ](ϑ−χ)(ζ−δ)1Γ(ℜ−1)∫10(1−υ)ℜ−2H(υ)dυ+χϑ−χm∑i=1Φi(Λ(ti))=∫t0[(t−υ)ℜ−1Γ(ℜ)+χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ+(ϑ−χ)δt(ϑ−χ)(ζ−δ)(1−υ)ℜ−2Γ(ℜ−1)]H(υ)dυ+∫1t[χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ+(ϑ−χ)δt(ϑ−χ)(ζ−δ)(1−υ)ℜ−2Γ(ℜ−1)]H(υ)dυ+1ϑ−χ∫10ϱ1(υ)Λ(υ)dυ+(ϑ−χ)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(s)Λ(υ)dυ+χϑ−χm∑i=1Φi(Λ(ti))=∫10ℵ(t,s)H(υ)dυ+1ϑ−χ∫10ϱ1(υ)Λ(υ)dυ+(ϑ−χ)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(υ)Λ(υ)dυ+χϑ−χm∑i=1Φi(Λ(ti)). |
Then,
∫10ϱ1(υ)∫10ℵ(υ,˜t)h(˜t)d˜tdυ=(1−Q1)∫10ϱ1(υ)Λ(υ)dυ−P1∫10ϱ2(υ)Λ(υ)dυ−A1χϑ−χ[m∑i=1Φi(Λ(ti))], |
∫10ϱ2(υ)∫10ℵ(υ,˜t)h(˜t)d˜tdυ=−Q2∫10ϱ1(υ)Λ(υ)dυ+(1−P2)∫10ϱ2(υ)Λ(υ)dυ−A2χϑ−χ[m∑i=1Φi(Λ(ti))], |
Hence,
∫10ϱ1(υ)Λ(υ)dυ=1Γ1[(1−P2)(∫10ϱ1(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A1χϑ−χm∑i=1Φi(Λ(ti)))+P1(∫10ϱ2(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A2χϑ−χm∑i=1Φi(Λ(ti)))], |
∫10ϱ2(υ)Λ(υ)dυ=1Γ1[Q2(∫10ϱ1(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A1χϑ−χm∑i=1Φi(Λ(ti)))+(1−Q1)(∫10ϱ2(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A2χϑ−χm∑i=1Φi(Λ(ti)))], |
which show that
Λ(t)=∫10ℵ(t,υ)H(υ)dυ+1ϑ−χ∫10ϱ1(υ)Λ(υ)dυ+(ϑ−χ)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(υ)Λ(υ)dυ+χϑ−χm∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+φ1(t)[∫10ϱ1(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A1χϑ−χm∑i=1Φi(Λ(ti))]+φ2(t)[∫10ϱ2(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A2χϑ−χm∑i=1Φi(Λ(ti))]+χϑ−χm∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10ϱn(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+Anχϑ−χm∑i=1Φi(Λ(ti))]+χϑ−χm∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10ϱn(˜t)∫10ℵ(˜t,υ)H(υ)dυd˜t+Anχϑ−χm∑i=1Φi(Λ(ti))]+χϑ−χm∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10H(υ)∫10ℵ(˜t,s)ϱn(˜t)d˜tdυ+Anχϑ−χm∑i=1Φi(Λ(ti))]+χϑ−χm∑i=1Φi(Λ(ti))=∫10[ℵ(t,υ)+2∑n=1φn(t)∫10ℵ(˜t,s)ϱi(˜t)d˜t]H(υ)dυ+[χϑ−χ+(2∑n=1χϑ−χAnφn(t))]m∑i=1Φi(Λ(ti))=∫10H1(t,υ)H(υ)dυ+m∑i=1H2(t,ti)Φi(Λ(ti)). |
Similar to the above process, for t∈Qκ=(tκ,tk+1], we have
Λ(t)=∫10ℵ(t,υ)H(υ)dυ+1ϑ−χ∫10ϱ1(υ)Λ(υ)dυ+(ϑ−χ)t+χ(ϑ−χ)(ζ−δ)∫10ϱ2(υ)Λ(υ)dυ+χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+φ1(t)[∫10ϱ1(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A1(χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti)))]+φ2(t)[∫10ϱ2(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+A2(χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti)))]+χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10ϱn(υ)∫10ℵ(υ,˜t)H(˜t)d˜tdυ+An(χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti)))]+χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10ϱn(t)∫10Φ(˜t,υ)H(υ)dυd˜t+An(χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti)))]+χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti))=∫10ℵ(t,υ)H(υ)dυ+2∑n=1φn(t)[∫10H(υ)∫10Φ(˜t,υ)ϱn(˜t)d˜tdυ+An(χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti)))]+χϑ−χm∑i=1Φi(Λ(ti))+κ∑i=1Φi(Λ(ti))=∫10[ℵ(t,υ)+2∑n=1φn(t)∫10ℵ(˜t,υ)ϱn(˜t)d˜t]H(υ)dυ+[χϑ−χ+(2∑n=1χϑ−χAnφn(t))]m∑i=k+1Φi(Λ(ti))+[ϑϑ−χ+(2∑n=1ϑϑ−χAnφn(t))]κ∑i=1Φi(Λ(ti))=∫10H1(t,υ)H(υ)dυ+m∑i=1H2(t,ti)Φi(Λ(ti)). |
The proof is completed.
We assume that the following condition is satisfied in this paper:
(H1) Q1<1, P2<1, (1−Q1)(1−P2)>P1Q2.
Lemma 2.4. The functions H1 and H2 have the following properties:
(1) for all t, υ∈[0,1], i=1, ⋯, m, H1(t,υ)≥0, H2(t,ti) >0;
(2) for all t, υ∈[0,1], d1M(υ) ≤ m(υ)≤ H1(t,υ) ≤ M(υ);
(3) for all t∈[0,1], i=1, ⋯, m, d2H2(1,0) ≤ H2(t,ti) ≤H2(1,0);
(4) for all υ∈[0,1], maxt∈[0,1] CtDℜ−10+H1(t,υ)≤1Γ(3−ℜ)M(υ);
(5) maxt∈[0,1] CtDℜ−10+H2(t,ti)≤ 1Γ(3−ℜ)H2(1,0), i=1, 2, ⋯, m,
where
M(υ)=g(υ)+2∑n=1φn(1)∫10ℵ(υ,˜t)ϱn(˜t)d˜t, |
m(υ)=d1g(υ)+2∑n=1φn(0)∫10ℵ(υ,˜t)ϱn(˜t)d˜t, |
g(υ)=χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+ϑδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)+1Γ(ℜ), |
Π=1+2∑n=1Anφn(0)1+2∑n=1Anφn(1), Π1=minυ∈[0,1][χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)], |
and d1=χΓ(ℜ)Π1ϑΓ(ℜ)Π1+χ, d2=χϑΠ.
Proof. First, it is easy to see that
H1(t,s), H2(t,ti)>0, |
for all t, υ∈[0,1], i=1, 2, ⋯, m. For given υ∈[0,1], we can get ℵ(t,υ) is increasing with respect to t for t∈Q by the definition of ℵ(t,υ). Then,
ℵ(t,υ)≤χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+ϑδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)+1Γ(ℜ)=g(υ), |
and
ℵ(t,υ)g(υ)≥χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)+(t−υ)ℜ−1Γ(ℜ)χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+ϑδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)+1Γ(ℜ)≥χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+ϑδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)+1Γ(ℜ)≥1ϑχ+1Γ(ℜ)[χ(1−υ)ℜ−1(ϑ−χ)Γ(ℜ)+χδ(1−υ)ℜ−2(ϑ−χ)(ζ−δ)Γ(ℜ−1)]≥1ϑχ+1Γ(ℜ)Π1=d1. |
Hence,
d1g(υ)≤ℵ(t,υ)≤g(υ), for all t, υ∈ [0,1], |
and
d1M(υ) ≤ m(υ)≤ H1(t,υ) ≤ M(υ), for all t, υ∈[0,1]. |
The proof of (3) is given below.
On the one hand, from the definition of H2(t,ti) and φn(t)(n=1,2), for 0≤t≤ti≤1, it is easily to see that
H2(t,ti)H2(1,0)=χϑ−χ+χϑ−χ2∑n=1Anφn(t)ϑϑ−χ+ϑϑ−χ2∑n=1Anφn(1)≥χϑ[1+2∑n=1Anφn(0)1+2∑n=1Anφn(1)]=χϑΠ=d2. |
On the other hand, for 0≤ti<t≤1, we get
H2(t,ti)H2(1,0)=ϑϑ−χ+ϑϑ−χ2∑n=1Anφn(t)ϑϑ−χ+ϑϑ−χ2∑n=1Anφn(1)>1+2∑n=1Anφn(0)1+2∑n=1Anφn(1)=Π. |
Therefore,
d2H2(1,0) ≤ H2(t,ti) ≤H2(1,0), |
for all t∈[0,1], i=1, 2, ⋯, m.
Next, by calculation, one can obtain that
CtDℜ−10+ℵ(t,υ)={δ(1−υ)ℜ−2t2−ℜ(ζ−δ)Γ(ℜ−1)Γ(3−ℜ)+1,0≤υ<t≤1;δ(1−υ)ℜ−2t2−ℜ(ζ−δ)Γ(ℜ−1)Γ(3−ℜ),0≤t≤υ≤1, |
CtDℜ−10+H1(t,υ)= CtDℜ−10+ℵ(t,υ)+2∑n=1[ CtDℜ−10+φn(t)]∫10ℵ(υ,˜t)ϱn(˜t)d˜t, |
and
CtDℜ−10+H2(t,υ)={χϑ−χ2∑n=1An[ CtDℜ−10+φn(t)],0≤t≤ti≤1;ϑϑ−χ2∑n=1An[ CtDℜ−10+φn(t)],0≤ti<t≤1. |
Hence,
maxt∈[0,1] CtDℜ−10+ℵ(t,υ)≤1Γ(3−ℜ)g(υ), for all υ∈[0,1], |
maxt∈[0,1] CtDℜ−10+H1(t,υ)≤1Γ(3−ℜ)M(υ), for all υ∈[0,1], |
maxt∈[0,1] CtDℜ−10+H2(t,ti)≤ 1Γ(3−ℜ)H2(1,0), i=1, 2, ⋯, m. |
Hence, (4) and (5) are valid.
Lemma 2.5. [19] The set Υ⊂PC([0,1],Rn) is relatively compact if and only if
(1) Υ is bounded, that is, ‖ϕ‖≤C for each ϕ∈Υ and some C>0.
(2) Υ is quasi-equicontinuous in (tκ−1,tκ](κ∈N), that is to say, for any ε>0, there exists δ>0 such that
|ϕ(t1)−ϕ(t2)|<ε |
for all ϕ∈Υ, t1,t2∈(tκ−1,tκ] with |t1−t2|<δ.
Let Ω be a nonempty open subset of a Banach space (X, ‖⋅‖). T:¯Ω→X is an operator, where T may be discontinuous.
Definition 2.6. [15] The closed-convex Krasovskij envelope (cc-envelope, for short) of an operator T:¯Ω→X is the multivalued mapping T:¯Ω→2X given by
TΛ=⋂ε>0¯coT(¯Bε(Λ)∩¯Ω) for every Λ∈¯Ω, |
where ¯co means closed convex hull, ¯Bε(Λ) is the closed ball centered at Λ and radius ε.
Lemma 2.7. [15] ˜Λ∈TΛ if for every ε>0 and every p>0 there exist m∈N and a finite family of vectors Λi∈¯Bε(Λ)∩¯Ω and coefficients πi∈[0,1](i=1,2,⋯,m) such that m∑i=1πi=1 and
‖˜Λ−m∑i=1πiTΛi‖<p. |
Next, we introduce Krasnoselskii's fixed point theorems for discontinuous operators on cones. Let P be a cone of Banach space X. Then, P defines the partial ordering in given by Λ≤˜Λ if and only if ˜Λ−Λ∈P. For Λ,˜Λ∈P, the set [Λ,˜Λ]={ˆΛ∈P:Λ≤ˆΛ≤˜Λ} is an order interval with Λ≤˜Λ. Denote PR={Λ∈P:‖Λ‖<R}, for given R>0.
Lemma 2.8. [16] Let R>0, 0∈Ωi⊂PR be relatively open subsets of P (i=1,2). T:¯PR→P is a mapping, where T¯PR is relatively compact and it fulfills condition
Λ∩TΛ⊂{TΛ} | (2.10) |
in ¯PR.
(a)For all Λ∈∂Ω1(λ≥1), if λΛ∉TΛ, then i(T, Ω1, P)=1.
(b)For every ℓ≥0 and all Λ∈P with Λ∈∂Ω2, if there exists ℓ∈P(ℓ≠0) such that Λ∉TΛ+ℓω, then i(T, Ω2, P)=0.
Lemma 2.9. [16] Assume that one of the following two conditions holds:
(i) ˜Λ≱Λ for all ˜Λ∈TΛ with Λ∈P and ‖Λ‖=r1.
(ii) ‖˜Λ‖<‖Λ‖ for all ˜Λ∈TΛ and all Λ∈P with ‖Λ‖=r1.
Then, Condition (a) in Lemma 2.8 is satisfied.
Analogously, if one of the following two conditions holds:
(i) ˜Λ≰Λ for all ˜Λ∈TΛ with Λ∈P and ‖Λ‖=r1.
(ii) If ‖˜Λ‖>‖Λ‖ for all ˜Λ∈TΛ and all Λ∈P with ‖Λ‖=r2.
Then, assumption (b) in Lemma 2.8 holds.
For the discontinuous nonlinearities ϝ, we define the admissible discontinuities curves.
Definition 2.10. We say that ℏ:Q→ R +, ℏ∈PC1(Q) is an admissible discontinuity curve for the differential system (1.1) if ℏ satisfies △ℏ′|t=ti=0(i=1, …, m), the boundary value conditions of (1.1) and one of the following conditions holds:
(i)
{ CtDℜ0+ℏ(t)=E(t)ϝ(t,ℏ(t)), a.e. t∈Q′,△ℏ|t=tκ=Φκ(ℏ(tκ)), κ=1, ⋯, m, | (2.11) |
(ii) there exist G, ¯G∈L1(J), G(t), ¯G(t)>0 a.e. for t∈[0,1], S, Θ⊂J, m(S∩Θ)=0, m(S∪Θ)>0, and ε>0 such that
{CtDℜ0+ℏ(t)+¯G(t)<E(t)ϝ(t,x), a.e. t∈Θ, x∈[ℏ(t)−ε,ℏ(t)+ε],CtDℜ0+ℏ(t)−G(t)>E(t)ϝ(t,x), a.e. t∈S, x∈[ℏ(t)−ε,ℏ(t)+ε],CtDℜ0+ℏ(t)=E(t)ϝ(t,ℏ(t)), a.e. t∈Q′∖(S∪Θ),△ℏ|t=tκ=Φκ(ℏ(tκ)), k=1, ⋯, m, | (2.12) |
(iii) there exist κ∈{1, 2, ⋯, m} such that
{CtDℜ0+ℏ(t)=E(t)ϝ(t,ℏ(t)), a.e. t∈Q′,△ℏ|t=tκ≠Φκ(ℏ(tκ)), | (2.13) |
(iv) there exists G, ¯G∈L1(Θ), G(t), ¯G(t)>0 a.e. for t∈[0,1], S, ˜Θ⊂Θ, m(S∩˜Θ)=0, m(S∪˜Θ)>0, and ε>0, κ∈{1, 2, ⋯, m} such that
{CtDℜ0+ℏ(t)+¯G(t)<E(t)ϝ(t,Λ), a.e. t∈Θ, x∈[ℏ(t)−ε,ℏ(t)+ε],CtDq0+ℏ(t)−G(t)>E(t)ϝ(t,x), a.e. t∈S, x∈[ℏ(t)−ε,ℏ(t)+ε],CtDq0+ℏ(t)=E(t)ϝ(t,ℏ(t)), a.e. t∈Q′∖(S∪Θ),△ℏ|t=tκ≠Φκ(ℏ(tκ)). | (2.14) |
Then, we assert that ℏ is viable for BVP (1.1) if (i) is satisfied; we say that ℏ is inviable if one of (ii)-(iv) is satisfied.
Let Ξ=PC1[0,1], P:={Λ∈Ξ:Λ(t)≥d‖Λ‖1, ∀t∈[0,1]}(d=Γ(3−ℜ)d3, d3=min{d1, d2}) and Pr:={Λ∈P: ‖Λ‖1≤r}. In order to apply Krasnoselskii's compression-expansion type fixed point theorems for discontinuous operators to BVP (1.1), we recall that if Λ is a solution of the following equation:
Λ(t)=∫10H1(t,s)E(s)ϝ(s,Λ(υ))dυ+m∑i=1H2(t,ti)Φi(Λ(ti)), | (3.1) |
then Λ∈Ξ is a solution of BVP (1.1).
Define an operator T:P→Ξ as follows:
TΛ(t):=∫10H1(t,s)E(s)ϝ(s,Λ(υ))dυ+m∑i=1H2(t,ti)Φi(Λ(ti)), Λ∈P. | (3.2) |
For any Λ∈P, TΛ is well defined by E∈L(0,1), the continuity of H1 and the assumption of ϝ. One can see that the existence of positive fixed points of T implies the existence of positive solutions for BVP (1.1).
Subsequently, let
N1=(∫10M(υ)g(υ)dυ)−1, N2=(∫10m(υ)g(υ)dυ)−1, |
N3=(supt∈[0,1]∫10 CtDℜ−10+H1(t,υ)g(υ)dυ)−1, N4=(inft∈[0,1]∫10 CtDℜ−10+H1(t,υ)g(υ)dυ)−1, |
N5=supt∈[0,1], i∈{1, ⋯,m}H2(t,ti), N6=inft∈[0,1], i∈{1, ⋯,m}H2(t,ti), |
N7=supt∈[0,1], i∈{1, ⋯,m} CtDℜ−10+H2(t,ti), N8=inft∈[0,1], i∈{1, ⋯,m} CtDℜ−10+H2(t,ti). |
Now, we are in position to give the assumptions satisfied throughout the paper.
(H2)ϝ:Q× R +→ R + satisfies:
(a) t∈Q↦ϝ(⋅,Λ) is measurable for any Λ∈ R +;
(b) For a.e. t∈Q and all Λ∈[0,r], there exists R>0 such that ϝ(t,Λ)≤R for each r>0.
(H3) E(t)≥0 almost everywhere for t∈[0,1] and E is measurable.
(H4) Admissible discontinuity curves ℏn:Q→ R +(n∈N) satisfy that the function Λ↦ϝ(t,Λ) is continuous in [0,∞)∖⋃n∈N{ℏn(t)} for a.e. t∈Q.
(H5) lim, \lim\limits_{\Lambda\rightarrow 0^{+}}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} > { }\frac{5}{4\mathfrak{d}}[{ }\frac{1}{ \mathcal {N}_{2}}+m\mathcal{N}_{6}]^{-1} ,
(H6) \lim\limits_{\Lambda\rightarrow +\infty}\sup \limits_ {t\in [0, 1]}{ }\frac{\digamma(t, \Lambda)}{\Lambda} < { }\frac{5}{6}[{ }\frac{1}{ \mathcal {N}_{1}}+m\mathcal{N}_{5}]^{-1} , \lim\limits_{\Lambda\rightarrow +\infty}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} < { }\frac{5}{6} [{ }\frac{1}{ \mathcal {N}_{1}}+m\mathcal{N}_{5}]^{-1} ,
(H7) \lim\limits_{\Lambda\rightarrow 0^{+}}\sup \limits_ {t\in[0, 1]}{ }\frac{\digamma(t, \Lambda)}{\Lambda} < { }\frac{5}{6}[{ }\frac{1}{ \mathcal {N}_{1}}+m\mathcal{N}_{5}]^{-1}, \ \lim\limits_{\Lambda\rightarrow 0^{+}}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} < { }\frac{5}{6} [{ }\frac{1}{ \mathcal {N}_{1}}+m\mathcal{N}_{5}]^{-1} ,
(H8) \lim\limits_{\Lambda\rightarrow +\infty}\inf \limits_ {t\in [0, 1]}{ }\frac{\digamma(t, \Lambda)}{\Lambda} > { }\frac{5}{4\mathfrak{d}}[{ }\frac{1}{ \mathcal {N}_{2}} +m\mathcal{N}_{6}]^{-1}, \ \lim\limits_{\Lambda\rightarrow +\infty}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} > { }\frac{5}{4\mathfrak{d}} [{ }\frac{1}{ \mathcal {N}_{2}}+m\mathcal{N}_{6}]^{-1} .
Lemma 3.1. The operator \mathcal{T}:\ \mathcal{P} \rightarrow \mathcal{P} is well-defined and maps bounded sets into relatively compact sets.
Proof. In view of the nonnegativity of \digamma, \ \mathcal {H}_{1}, \ \mathcal {H}_{2} , \Phi_{{\kappa}}({\kappa} = 1, \ \cdots, \ m) and \mathcal {E}(t)\geq 0 for a.e.\ t\in\ Q , we conclude that \mathcal{T}\Lambda(t)\geq0 for t\in [0, 1]. Hence, \mathcal{T}:\ \mathcal{P} \rightarrow \mathcal{P} is well-defined.
Then, by calculation, for \Lambda\in P, it is easy to see
\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}(\mathcal{T}\Lambda) (t) = \int_{0}^{1}[\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{1}(t, {\upsilon})] \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m}[\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{2}(t, t_{i})] \Phi_{i}(\Lambda(t_{i})), |
where
_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\aleph(t, {\upsilon}) = \begin{cases}{ } \frac{{\zeta}(1-{\upsilon})^{\Re -2}t^{2-\Re }}{({\zeta}-{\delta})\Gamma(\Re -1)\Gamma(3-\Re )}+1, &{ 0\leq {\upsilon} < t\leq 1 };\\ { }\frac{{\zeta}(1-{\upsilon})^{\Re -2}t^{2-\Re }}{({\zeta}-{\delta})\Gamma(\Re -1)\Gamma(3-\Re )}, &{ 0\leq t \leq {\upsilon}\leq 1 }, \end{cases} |
_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{1}(t, {\upsilon}) = \ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\aleph(t, {\upsilon})+\sum\limits_{n = 1}^{2} [\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\varphi_{n}(t)]\int_{0}^{1} \aleph({\upsilon}, \widetilde{t})\varrho_{n}(\widetilde{t})d\widetilde{t} , |
and
_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{2}(t, t_{i}) = \begin{cases}{ }\frac{{\chi}}{{\vartheta}-{\chi}} \sum\limits_{n = 1}^{2}\mathfrak{A}_{n}[\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\varphi_{n}(t)] , &{ 0\leq t \leq t_{i}\leq 1 };\\ { }\frac{{\vartheta}}{{\vartheta}-{\chi}}\sum\limits_{n = 1}^{2}\mathfrak{A}_{n}[\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\varphi_{n}(t)] , &{ 0\leq t_{i} < t \leq 1 }.\end{cases} |
By Lemma 2.4, one can get that
\begin{array}{l} \mathfrak{d}\|_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {T} \Lambda\|_{0}& = &\mathfrak{d}\ max_{t\in[0, 1]}[\int_{0}^{1}(_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{1}(t, {\upsilon})) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon}\\ &&+\sum\limits_{i = 1}^{m}( _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{2}(t, t_{i})) \Phi_{i}(\Lambda(t_{i}))]\\ &\leq&\mathfrak{d}_{3}[\int_{0}^{1} \mathcal {M}({\upsilon}) \mathcal {E}({\upsilon}) \digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(1, 0) \Phi_{i}(\Lambda(t_{i}))]\\ &\leq&\int_{0}^{1}m({\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon} +\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(0, 1)\Phi_{i}(\Lambda(t_{i}))\\ & = &min_{t\in[0, 1]}\mathcal{T}\Lambda({\tau}). \end{array} |
Thinking about it from the other side, we have
\begin{array}{l} \mathfrak{d}\| \mathcal {T}\Lambda\|_{0}&\leq&\mathfrak{d}_{3} [\int_{0}^{1} \mathcal {M}({\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon} +\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(1, 0)\Phi_{i}(\Lambda(t_{i}))]\\ &\leq&\int_{0}^{1}m({\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda({\upsilon}))d{\upsilon} +\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(0, 1)\Phi_{i}(\Lambda(t_{i}))\\ & = &min_{t\in[0, 1]} \mathcal {T}\Lambda(t). \end{array} |
Therefore,
min_{t\in[0, 1]} \mathcal {T}\Lambda(t)\geq\mathfrak{d}({\upsilon})\ max\{\| \mathcal {T}\Lambda\|_{0}, \|\ _{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}} \mathcal {T}\Lambda\|_{0}\} = \mathfrak{d}({\upsilon})\| \mathcal {T}\Lambda\|_{1}. |
Next, we notice that there exists \mathcal{M}_{{\kappa}} > 0 such that
\Phi_{{\kappa}}(\Lambda)\leq \mathcal{M}_{{\kappa}}, \ for\ \Lambda\in [0, r], |
where {\kappa} = 1, \ 2, \ \cdots, \ m for each r > 0 . Therefore, \mathcal {T}(\mathcal {P}_{r}) is bounded by (H2).
Moreover, we have
_{t}^{C} \mathcal {D} ^{q}_{0^{+}} \mathcal {T}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda(t))\leq R \mathcal {E}(t), |
for any \Lambda\in \mathcal {P}_{r} and a.e. t\in Q_{{\kappa}} .
Therefore,
|_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}( \mathcal {T}\Lambda)(\widehat{t}_{2})-\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}( \mathcal {T}\Lambda)(\widehat{t}_{1})|\leq\int_{\widehat{t}_{1}}^{\widehat{t}_{2}}|_{r}^{C}D^{q}_{0^{+}}( \mathcal {T}\Lambda)(r)|dr\\ \leq\int_{\widehat{t}_{1}}^{\widehat{t}_{2}}R \mathcal {E}(r)dr, |
where \widehat{t}_{1}, \ \widehat{t}_{2}\in Q_{{\kappa}} . Hence, \mathcal{T}(\mathcal {P}_{r}) is relatively compact.
Lemma 3.2. Let \mathbb{T} be the cc-envelope of the operator \mathcal{T} : \mathcal {P}_{R} \rightarrow \mathcal{P} . If (H4) is satisfied, then
{\Lambda} \cap \mathbb{T}\Lambda \subset \{ \mathcal {T}\Lambda\}, \ for\ all\ \Lambda\in {\mathcal{P}}_{R}. |
Proof. Let \mathfrak{W}_{n} = \{t \in Q: \Lambda(t) = \hbar_{n}(t)\}(n\in { \mathbb{N} }) . Fix \Lambda \in \mathcal {P}_{R} and we think about three cases below.
Case 1: m(\mathfrak{W}_{n}) = 0 for all n \in { \mathbb{N} } .
If \Lambda_{{\kappa}} \rightarrow \Lambda in \mathcal {P}_{R} , by (H4), it is easy to see that \digamma(t, \Lambda_{{\kappa}}(t)) \rightarrow \digamma(t, \Lambda(t)) for a.e. t \in Q . This, together with (H2) and (H3), implies that
\mathcal {T}\Lambda_{{\kappa}} \rightarrow \mathcal {T}\Lambda\ {\rm in}\ \mathcal {P}_{R}. |
Hence \mathcal{T} is continuous at \Lambda . Hence, \mathbb{T}\Lambda = { \mathcal {T}\Lambda} .
Case 2: there exists n \in { \mathbb{N} } such that \hbar_{n} is inviable and m(\mathfrak{W}_{n}) > 0 . Let \mathbb {B} = \{n: m(\mathfrak{W}_{n}) > 0, \ \hbar_{n}\ is\ inviable\} . Case 2 will be demonstrated in three subcases.
Case 2.1: The above \hbar_{n} satisfies (ii) in Definition 2.10.
By (ii) in Definition 2.10, there exist \mathcal {G}, \ \overline{ \mathcal {G}}\in L^{1}(Q'), \ \mathcal {G}(t), \ \overline{ \mathcal {G}}(t) > 0\ for\ a.e.\ t\in[0, 1] , S_{n}, \ \Theta_{n}\subset Q, m(S_{n}\cap \Theta_{n}) = 0 , m(S_{n}\cup \Theta_{n}) > 0 , and \varepsilon > 0 such that
\begin{equation} \left\{ \begin{array}{l} _{t}^{C} \mathcal {D} ^{\Re }_{0^{+}}\hbar(t)+\overline{ \mathcal {G}}(t) < \mathcal {E}(t)\digamma(t, \hbar_{n}(t)), \ a.e.\ t\in \Theta_{n}, \ \Lambda\in [\hbar_{n}(t)-\varepsilon, \hbar_{n}(t)+\varepsilon], \\ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\hbar(t)- \mathcal {G}(t) > \mathcal {E}(t)\digamma(t, \hbar_{n}(t)), \ a.e.\ t\in S_{n}, \ \Lambda\in [\hbar_{n}(t)-\varepsilon, \hbar_{n}(t)+\varepsilon], \\ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\hbar(t) = \mathcal {E}(t)\digamma(t, \hbar_{n}(t)), \ a.e.\ t\in Q'\setminus(S_{n}\cup \Theta_{n}), \\ \triangle\hbar_{n}|_{t = t_{{\kappa}}} = \Phi_{{\kappa}}(\hbar_{n}(t_{{\kappa}})), \ {\kappa} = 1, \ \cdots, \ m.\end{array} \right. \end{equation} | (3.3) |
(I) m(\{t\in S_{n}\cup \Theta_{n}|\Lambda(t) = \hbar_{n}(t)\}) = 0 for all n\in \mathbb {B} .
By m(\{t\in S_{n}\cup \Theta_{n}|\Lambda(t) = \hbar_{n}(t)\}) = 0 , for a.e.\ t\in \mathfrak{W}_{n} , one can obtain that
_{t}^{C} \mathcal {D}^{\Re }_{0^{+}} \hbar_{n}(t) = \mathcal {E}(t)\digamma(\Lambda, \hbar_{n}(t)). |
This is,
_{t}^{C} \mathcal {D} ^{\Re }_{0^{+}}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda), \ t\in \bigcup\limits_{n\in \mathbb {B}}\mathfrak{W}_{n}. |
For each {\kappa} \in { \mathbb{N} } , on account of \Lambda \in \mathbb{T}\Lambda , there exist functions \Lambda_{p, i} \in B_{\frac{1}{p}}(\Lambda)\cap \mathcal {P}_{R} and coefficients \lambda_{p, i} \in [0, 1] (i = 1, \ 2, \cdots, \ m(p)) such that
\sum\limits_{i = 1}^{m(p)}\lambda_{p, i} = 1, |
and
\|\Lambda-\sum\limits_{i = 1}^{m(p)}\lambda_{p, i} \mathcal {T}\Lambda_{p, i}\| < { }\frac{1}{p}, |
by Lemma 2.7 with \varepsilon = \mathfrak{p} = { }\frac{1}{p} .
Denote V_{p} = \sum\limits_{i = 1}^{m(p)}\lambda_{p, i} \mathcal {T}\Lambda_{p, i}. If p\rightarrow \ \infty in Q , we can see that V_{p}\rightarrow \Lambda uniformly.
For a.e.\ t \in Q \setminus \bigcup\limits_{n\in \mathbb {B}}\mathfrak{W}_{n} , one can see that \mathcal {E}(t)\digamma(t, \cdot) is continuous at \Lambda(t) . Consequently, for any \varepsilon > 0 , there is some p_{0} = p(t) \in { \mathbb{N} } such that, for all {\kappa} \in { \mathbb{N} } , p \geq p_{0} , we have
| \mathcal {E}(t)\digamma(t, \Lambda_{p, i}(t))- \mathcal {E}(t)\digamma(t, \Lambda(t))| < \varepsilon, |
for all i\in\{1, \ 2, \ \cdots, \ m(p)\} . Then,
| _{t}^{C} \mathcal {D} ^{\Re }_{0^{+}}V_{p}(t)- \mathcal {E}(t)\digamma(t, \Lambda(t))|\leq\sum\limits_{i = 1}^{m(p)}\lambda_{p, i} | \mathcal {E}(t)\digamma(t, \Lambda_{p, i}(t))- \mathcal {E}(t)\digamma(t, \Lambda(t))| < \varepsilon. |
This is,
_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}V_{p}(t)\rightarrow \mathcal {E}(t)\digamma(t, \Lambda(t)), \ {\rm when}\ p\rightarrow \infty, |
for a.e.\ t \in Q \setminus \bigcup\limits_{n\in \mathbb {B}}\mathfrak{W}_{n} .
On the other hand,
\begin{array}{l} |_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}V_{p}(t)-\ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t)|& = &{ }\frac{1} {\Gamma(\Re )}|\int_{0}^{t}(t-{\upsilon})^{\Re -1}V_{p}({\upsilon})d{\upsilon} -\int_{0}^{t}(t-{\upsilon})^{\Re -1}\Lambda({\upsilon})d{\upsilon}|\\ &\leq&{ }\frac{1}{\Gamma(\Re )}\int_{0}^{t} (t-{\upsilon})^{\Re -1}|V_{p}({\upsilon})-\Lambda({\upsilon})|d{\upsilon}\\ &\leq&\varepsilon_{1}({ }\frac{1}{\Gamma(\Re )} \int_{0}^{t}(t-{\upsilon})^{\Re -1}d{\upsilon})\\ &\leq&{ }\frac{1}{\Gamma(\Re +1)}\varepsilon_{1}, \end{array} |
which guarantees that _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda) for a.e.\ t\in Q \setminus\bigcup\limits_{n\in \mathbb {B}}\mathfrak{W}_{n}. The process above implies \Lambda = \mathcal {T}\Lambda if \Lambda \in \mathbb{T}\Lambda .
(II) There exists n\in \mathbb {B} such that m(\{t\in S_{n}\cup \Theta_{n}|\Lambda(t) = \hbar_{n}(t)\}) > 0 .
Suppose m(\{t\in S_{n}|\Lambda(t) = \hbar_{n}(t)\}) > 0 . Now we are in position to prove
\Lambda\notin \mathbb{T}\Lambda. |
For a.e.\ t\in Q , by (H2), there exists \mathcal{H}_{R} > 0 such that \digamma(t, \Lambda(t)) < \mathcal{H}_{R} . Let F(t) = \mathcal {E}(t)\mathcal{H}_{R} and \mathcal{A} = \{t\in S_{n}|\ \Lambda(t) = \hbar_{n}(t)\}(n\in { \mathbb{N} }) . There exists an interval Q_{{\kappa}_{0}}({\kappa}_{0}\in\{1, \ \cdots, \ m\}) such that m(Q_{k_{0}}\cap \mathcal{A}) > 0 . Let \mathbb{A} = Q_{k_{0}}\cap \mathcal{A} . On account of F \in L(Q) and Lemma 3.8 in [15], there is a measurable set A_{0} \subset \mathbb{A} with m(A_{0}) = m(\mathbb{A}) > 0 such that, we obtain
\begin{equation} lim_{t\rightarrow \widehat{t}_{0}^{+}}{ }\frac{2\int_{[\widehat{t}_{0}, t]\setminus \mathbb{A}}F( {\upsilon})d{\upsilon}}{{ }\frac{1}{4}\int_{\widehat{t}_{0}}^{t} \mathcal {G}( {\upsilon})d{\upsilon}} = 0 = lim_{t\rightarrow \widehat{t}_{0}^{-}}{ }\frac{2\int_{[t, \widehat{t}_{0}]\setminus \mathbb{A}}F( {\upsilon})d{\upsilon}}{{ }\frac{1}{4}\int^{\widehat{t}_{0}}_{t} \mathcal {G}( {\upsilon})d{\upsilon}}, \end{equation} | (3.4) |
for all \widehat{t}_{0} \in A_{0} .
Moreover, by Corollary 3.9 in [15], there exists A_{1}\subset A_{0} with m(A_{0}\setminus A_{1}) = 0 such that,
\begin{equation} lim_{t\rightarrow \widehat{t}_{0}^{+}}{ }\frac{\int_{[\widehat{t}_{0}, t]\cap A_{0}} \mathcal {G}( {\upsilon})d{\upsilon}}{\int_{\widehat{t}_{0}}^{t} \mathcal {G}( {\upsilon})d{\upsilon}} = 1 = lim_{t\rightarrow \widehat{t}_{0}^{-}}{ }\frac{\int_{[t, \widehat{t}_{0}]\cap A_{0}} \mathcal {G}( {\upsilon})d{\upsilon}}{\int_{\widehat{t}_{0}}^{t} \mathcal {G}( {\upsilon})d{\upsilon}}, \end{equation} | (3.5) |
for all \widehat{t}_{0} \in A_{1} .
Fix a point \widehat{t}_{0}\in A_{1} . By (3.4) and (3.5), we konw that t_{-} < \widehat{t}_{0} , t_{+} > \widehat{t}_{0} exist with t_{+}, \ t_{-} \rightarrow \widehat{t}_{0} . Moreover, t_{+}, \ t_{-} satisfies the following inequalities.
\begin{equation} 2\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}}F({\upsilon})d{\upsilon} < { }\frac{1}{4}\int_{\widehat{t}_{0}}^{t_{+}} \mathcal {G}({\upsilon})d{\upsilon}, \end{equation} | (3.6) |
\begin{equation} \int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}} \mathcal {G}({\upsilon})d{\upsilon}\geq\int_{[\widehat{t}_{0}, t^{+}]\cap A_{0}} \mathcal {G}({\upsilon})d{\upsilon} > { }\frac{1}{2}\int_{\widehat{t}_{0}}^{t_{+}} \mathcal {G}({\upsilon})d{\upsilon}, \end{equation} | (3.7) |
\begin{equation} 2\int_{[t^{-}, \widehat{t}_{0}]\setminus \mathbb{A}}F({\upsilon})d{\upsilon} < { }\frac{1}{4}\int^{\widehat{t}_{0}}_{t_{-}} \mathcal {G}({\upsilon})d{\upsilon}, \end{equation} | (3.8) |
\begin{equation} \int_{[t^{-}, \widehat{t}_{0}]\cap \mathbb{A}} \mathcal {G}({\upsilon})d{\upsilon} > { }\frac{1}{2}\int^{\widehat{t}_{0}}_{t_{-}} \mathcal {G}({\upsilon})d{\upsilon}. \end{equation} | (3.9) |
Now we will prove that \Lambda \notin \mathbb{T}\Lambda .
Claim: For every finite family \Lambda_{i} \in B_{\varepsilon}(\Lambda) \cap \overline{B}_{R} and \pi_{i} \in [0, 1]\ (i = 1, 2, \ \cdots, m_{1}), there exists \mathfrak{p} > 0 such that
\|\Lambda-\sum\limits_{i = 1}^{m_{1}}\pi_{i} \mathcal {T}\Lambda_{i}\| \geq\mathfrak{p}, |
where \sum\limits_{i = 1}^{m_{1}} \pi_{i} = 1 .
Denote V = \sum\limits_{i = 1}^{m_{1}} \pi_{i} \mathcal {T}\Lambda_{i} . Then for a.e. t \in \mathbb{A} , we have
\begin{equation} _{t}^{C} \mathcal {D}^{\Re }_{0^{+}} v(t) = \sum\limits_{i = 1}^{m_{1}}\pi_{i}\ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}( \mathcal {T}\Lambda_{i})(t) = \sum\limits_{i = 1}^{m_{1}}\pi_{i} \mathcal {E}(t)\digamma(t, \Lambda_{i}(t)). \end{equation} | (3.10) |
For every i\in \{1, \ 2, \ \cdots, \ m_{1}\} and t\in \mathbb{A} , one can obtain that
|\Lambda_{i}(t)-\hbar_{n}(t)| = |\Lambda_{i}(t)-\Lambda(t)| < \varepsilon. |
Then, for a.e. t\in A , we have
\begin{equation} _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}V(t) = \sum\limits_{i = 1}^{m_{1}} \pi_{i} \mathcal {E}(t)\digamma(t, \Lambda_{i}(t)) < \sum\limits_{i = 1}^{m_{1}}\pi_{i}(_{t}^{C} \mathcal {D} ^{\Re }_{0^{+}}\hbar_{n}(t)- \mathcal {G}(t)) = \ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t)- \mathcal {G}(t). \end{equation} | (3.11) |
Now we compute
\begin{array}{l} _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}V(t^{+})-\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} V(\widehat{t}_{0}) & = &\int_{\widehat{t}_{0}}^{t^{+}}[_{s}^{C} \mathcal {D}^{\Re -1}_{0^{+}}V({\upsilon})]'d{\upsilon} = \int_{\widehat{t}_{0}}^{t^{+}}[_{s}^{C} \mathcal {D} ^{\Re }_{0^{+}}V({\upsilon})]d{\upsilon}\\ & = &\int_{[\widehat{t}_{0}, t^{+}]\cap \mathbb{A}}[_{s}^{C} \mathcal {D}^{\Re }_{0^{+}}V({\upsilon})]d{\upsilon}+\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}}[_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}V({\upsilon})]d{\upsilon}\\ & < &\int_{[\widehat{t}_{0}, t^{+}]\cap \mathbb {A}}\ _{s}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda({\upsilon})d{\upsilon} -\int_{[\widehat{t}_{0}, t^{+}]\cap \mathbb {A}} \mathcal {G}({\upsilon})d{\upsilon}\\ &&+\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}}F({\upsilon})d{\upsilon}\\ & = &\ _{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}}\Lambda(t^{+})-\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \Lambda(\widehat{t}_{0})-\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}}\ _{s}^{C} \mathcal {D}^{\Re }_{0^{+}} \Lambda({\upsilon})d{\upsilon}\\ &&-\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb{A}} \mathcal {G}(s)d{\upsilon} +\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb {A}}F({\upsilon})d{\upsilon}\\ &\leq&\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\Lambda(t^{+})-\ _{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}} \Lambda(\widehat{t}_{0})-\int_{[\widehat{t}_{0}, t^{+}]\cap \mathbb {A}} \mathcal {G}({\upsilon})d{\upsilon}\\ &&+2\int_{[\widehat{t}_{0}, t^{+}]\setminus \mathbb {A}}F({\upsilon})d{\upsilon}\\ & < &\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\Lambda(t^{+})-\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \Lambda(\widehat{t}_{0})-{ }\frac{1}{4}\int_{\widehat{t}_{0}}^{t^{+}} \mathcal {G}({\upsilon})d{\upsilon}. \end{array} |
Choosing
\begin{equation} \mathfrak{p} = min\{{ }\frac{1}{4}\int_{t_{-}}^{\widehat{t}_{0}} \mathcal {G}({\upsilon})d{\upsilon}, { }\frac{1}{4}\int^{t_{+}}_{\widehat{t}_{0}} \mathcal {G}({\upsilon})d{\upsilon}\}. \end{equation} | (3.12) |
Hence, \|\Lambda-V\|_{1}\geq \ _{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}}\Lambda(t^{+})-\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}V(t^{+})\geq \mathfrak{p} , provided that _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\Lambda(\widehat{t}_{0})\geq\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}V(\widehat{t}_{0}).
Using t_{-} instead of t_{+} , we can get that
_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\Lambda(\widehat{t}_{0})\leq\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}v(\widehat{t}_{0}), |
by similar progress. Hence, we have \|\Lambda-V\|_{1}\geq \mathfrak{p} . The claim is proven.
By Lemma 2.7, one can see that \Lambda \notin \mathbb{T}\Lambda .
Case 2.2: The above \hbar_{n} satisfies (iii) in Definition 2.4. Let \mathbb {B}_{1} = \{n: m(\mathfrak{W}_{n}) > 0, \ \hbar_{n}\ satisfies\ (iii)\ in\ Definition\ 2.4\}.
Then, there exist k\in\{1, \ 2, \ \cdots, \ m\} such that
\begin{equation} \left\{ \begin{array}{l} _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\hbar(t) = \mathcal {E}(t)\digamma(t, \hbar_{n}(t)), \ a.e.\ t\in Q';\\ \triangle\hbar_{n}|_{t = t_{{\kappa}}}\neq \Phi_{{\kappa}}(\hbar_{n}(t_{{\kappa}})), \ {\kappa} = 1, \ \cdots, \ m.\end{array} \right. \end{equation} | (3.13) |
We suppose that there exist Y, \ \varepsilon > 0 such that \triangle\hbar_{n}|_{t = t_{{\kappa}}}+Y < \Phi_{{\kappa}}(z), \ z\in[\hbar_{n}(t_{{\kappa}})-\varepsilon, \hbar_{n}(t_{{\kappa}})+\varepsilon] by the continuity of \Phi_{{\kappa}} .
(I) \Lambda(t_{{\kappa}})\neq\hbar_{n}(t_{{\kappa}}) or \Lambda(t_{{\kappa}}^{+})\neq\hbar_{n}(t_{{\kappa}}^{+}) .
By (2.13), for a.e.\ t\in \bigcup_{n\in \mathbb {B}_{1}}\mathfrak{W}_{n} , we have _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda(t)). Similar to the proof of (I) in Case 2.1, it is easy to see that \Lambda \notin \mathbb{T}\Lambda or \Lambda = \mathcal {T}\Lambda if \Lambda \in \mathbb{T}\Lambda . Hence, {\Lambda} \cap \mathbb{T}\Lambda \subset \{ \mathcal {T}\Lambda\} for all \Lambda\in {\mathcal{P}}_{R}.
(II) When \Lambda(t_{{\kappa}}) = \hbar_{n}(t_{{\kappa}}) and \Lambda(t_{{\kappa}}^{+}) = \hbar_{n}(t_{{\kappa}}^{+}) , we assert that \Lambda \notin \mathbb{T}\Lambda .
Claim: Let \varepsilon > 0 and \mathfrak{p} = { }\frac{Y}{2} , for every finite family \Lambda_{i} \in B_{\epsilon}(\Lambda) \cap \mathcal {P}_{R} and \pi_{i} \in [0, 1] (i = 1, 2, \ \cdots, m_{1}) with \sum\limits_{i = 1}^{m_{1}}\pi_{i} = 1 , we have
\|\Lambda-\sum\limits_{i = 1}^{m_{1}}\pi_{i} \mathcal {T}\Lambda_{i}\|\geq\mathfrak{p}. |
For simplicity, denote V = \sum\limits_{i = 1}^{m_{1}} \pi_{i} \mathcal {T}\Lambda_{i} . In view of |\Lambda_{i}(t_{{\kappa}})-\Lambda(t_{{\kappa}})| = |\Lambda_{i}(t_{{\kappa}})-\hbar_{n}(t_{{\kappa}})| < \varepsilon_{1} , one can get
\begin{array}{l} \triangle V|_{t = t_{{\kappa}}}& = &\sum\limits_{i = 1}^{m_{1}}\pi_{i}(\triangle \mathcal {T}\Lambda_{i}|_{t = t_{{\kappa}}}) = \sum\limits_{i = 1}^{m_{1}}\pi_{i}(\Phi_{{\kappa}}(\Lambda_{i}(t_{{\kappa}})))\\ & > &\sum\limits_{i = 1}^{m_{1}}\pi_{i}(\triangle\hbar_{n}|_{t = t_{{\kappa}}}+Y)\\ & = &\triangle\hbar_{n}|_{t = t_{{\kappa}}}+Y\\ & = &\triangle \Lambda|_{t = t_{{\kappa}}}+Y, \end{array} |
which implies that
V(t_{{\kappa}}^{+})-\Lambda(_{{\kappa}}^{+}) > V(t_{{\kappa}})-\Lambda(t_{{\kappa}})+\Lambda\geq-|V(t_{{\kappa}})-\Lambda(t_{{\kappa}})|+Y. |
That is
\|\Lambda-V\|_{1}\geq{ }\frac{Y}{2}. |
The claim is proven.
Case 2.3: The above \hbar_{n} satisfies (iv) in Definition 2.10.
Hence, one can also obtain that
{\Lambda} \cap \mathbb{T}\Lambda \subset \{ \mathcal {T}\Lambda\}, \ for\ all\ \Lambda\in {\mathcal{P}}_{R}. |
by the process similar to proving Case 2.1 and Case 2.2.
Case 3: m(\{\mathfrak{W}_{n}\}) > 0 for n \in { \mathbb{N} } such that \hbar_{n} is viable.
For each n \in { \mathbb{N} } and a.e. t \in \mathfrak{W}_{n} ,
_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t) = \ _{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\hbar_{n}(t) = \mathcal {E}(t)\digamma(t, \hbar_{n}(t)) = \mathcal {E}(t)\digamma(t, \Lambda(t)). |
Therefore,
_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda(t)) \ {\rm a.e.\ in}\ \mathbb{B} = \bigcup\limits_{n\in { \mathbb{N} }}\mathfrak{W}_{n}. |
If \Lambda \in \mathbb{T}\Lambda , we can obtain that
_{t}^{C} \mathcal {D}^{\Re }_{0^{+}}\Lambda(t) = \mathcal {E}(t)\digamma(t, \Lambda(t))\ {\rm a.e.\ in}\ Q\setminus \mathbb{B}, |
by the process of proving (I) in Case 2.1. Hence, \Lambda = \mathcal {T}\Lambda .
Theorem 3.3. If (H1)–(H6) hold, then BVP (1.1) admits at least one positive solution.
Proof. Claim 1: For all \widetilde{\Lambda} \in \mathbb{T}\Lambda and \Lambda\in P , there exists r_{1} > 0 such that \widetilde{\Lambda} \nleq\Lambda , where \|\Lambda\| = \mathfrak{r}_{1} .
In fact, the condition (H5) means that there exist \widetilde{\varepsilon}_{0} , {\mathfrak{r}}_{1} > 0 such that
\begin{equation} \digamma(t, \Lambda) > (\lambda+\widetilde{\varepsilon}_{0})\Lambda, \ \Phi_{{\kappa}}(\Lambda) > (\lambda+\widetilde{\varepsilon}_{0})\Lambda, \ t\in[0, 1], \ \Lambda\in[0, { }\frac{6}{5}{\mathfrak{r}}_{1}]. \end{equation} | (3.14) |
Suppose \Lambda \in P with \|\Lambda\|_{1} = {\mathfrak{r}}_{1} . For every finite family \Lambda_{i} \in B_{\epsilon}(\Lambda) \cap P and \pi_{i} \in [0, 1] (i = 1, \ 2, \ \cdots, \ m_{2}) , with \sum\limits_{i = 1}^{m_{2}} \pi_{i} = 1 , and \epsilon\in[0, { }\frac{{\mathfrak{r}}_{1}}{5}] , one can obtain that
\begin{array}{l} \widetilde{\Lambda}(t)& = &\sum\limits_{i = 1}^{m_{2}}\pi_{i} \mathcal {T}\Lambda_{i}(t)\\ & = &\sum\limits_{i = 1}^{m_{2}}\pi_{i}[\int_{0}^{1} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda_{i}({\upsilon}))d{\upsilon} +\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}(\Lambda_{i}(t_{i}))]\\ & > &\sum\limits_{i = 1}^{m_{2}}\pi_{i}(\lambda +\widetilde{\varepsilon}_{0}) [\int_{0}^{1} \mathcal {H}_{1}(t, {\upsilon}){\mathfrak{g}}({\upsilon})\Lambda_{i}({\upsilon})d{\upsilon} +\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(t, t_{i}) \Lambda_{i}(t_{i})]\\ &\geq&\sum\limits_{i = 1}^{m_{2}}\pi_{i}(\lambda +\widetilde{\varepsilon}_{0})[{ }\frac{\mathfrak{d}({\upsilon})\| \Lambda_{i}\|_{1}}{ \mathcal {N}_{2}}+m \mathcal {N}_{6}\mathfrak{d}({\upsilon})\|\Lambda_{i}\|_{1}]\\ &\geq&\mathfrak{d}({\upsilon})(\|\Lambda\|_{1}-\epsilon) (\lambda+\widetilde{\varepsilon}_{0})[{ }\frac{1}{ \mathcal {N}_{2}}+m \mathcal {N}_{6}]\\ & > &{\mathfrak{r}}_{1} = \|\Lambda\|_{1}. \end{array} |
This implies that \widetilde{\Lambda}\nleq\Lambda for all \widetilde{\Lambda } \in \mathbb{T}\Lambda with \Lambda \in \mathcal{P} and \|\Lambda\|_{1} = {\mathfrak{r}}_{1} . By Lemma 2.8 and 2.9, we get
\begin{equation} \ i(\mathcal{T}, \mathcal{P}\cap\partial B_{{\mathfrak{r}}_{1}}, \mathcal{P}) = 0. \end{equation} | (3.15) |
Claim 2: There exists \Re _{1} > {\mathfrak{r}}_{1} > 0 such that \|\widetilde{\Lambda}\|_{1} < \|\Lambda\|_{1} for all \widetilde{\Lambda} \in \mathbb{T}\Lambda and all \Lambda \in P with \|\Lambda\|_{1} = \Re _{1} .
In fact, the assumption (H6) implies that there exists 0 < \varepsilon_{1} < \widetilde{\lambda} such that
\digamma(t, \Lambda) < (\widetilde{\lambda}-\varepsilon_{1})\Lambda, \ \Phi_{{\kappa}}(\Lambda) < (\widetilde{\lambda}-\varepsilon_{1})\Lambda, \ t\in[0, 1], \ \Lambda\geq { }\frac{4}{5}\mathcal{R}_{1}. |
Choosing \Re _{1} > max\{{\mathfrak{r}}_{1}, \ { }\frac{4\mathcal{R}_{1}}{5\mathfrak{d}({\upsilon})} \} , for \Lambda\in \partial \mathcal {P}_{\Re _{1}} , one can see that
\Lambda(t)\geq\mathfrak{d}({\upsilon})\|\Lambda\|_{1} = \mathfrak{d}({\upsilon}) \Re _{1} > { }\frac{4}{5}\mathcal{R}. |
Suppose \Lambda \in P with \|\Lambda\|_{1} = \Re _{1} . For \pi_{i} \in [0, 1](i = 1, \ 2, \ \cdots, \ m_{3}) , with \sum\limits_{i = 1}^{m_{3}} \pi_{i} = 1 and every finite family \Lambda_{i} \in B_{\epsilon}(\Lambda) \cap P , \epsilon\in[0, { }\frac{{\mathfrak{r}}_{1}}{5}] , one can see that
\begin{array}{l} \widetilde{\Lambda}(t)& = &\sum\limits_{i = 1}^{m_{3}}\pi_{i} \mathcal {T}\Lambda_{i}(t)\\ & = &\sum\limits_{i = 1}^{m_{3}}\pi_{i}[\int_{0}^{1} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda_{i}({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}(\Lambda_{i}(t_{i}))]\\ & < & \sum\limits_{i = 1}^{m_{3}}\pi_{i}[\int_{0}^{1} \mathcal {H}_{1} (t, {\upsilon}) {\mathfrak{g}}({\upsilon})(\widetilde{\lambda}-\varepsilon_{1})\Lambda_{i}({\upsilon})d{\upsilon} +\sum\limits_{i = 1}^{m_{3}} \mathcal {H}_{2}(t, t_{i})] (\widetilde{\lambda}-\varepsilon_{1})\Lambda_{i}(t_{i})\\ &\leq&(\Re _{1}+\epsilon)(\widetilde{\lambda} -\varepsilon_{1})[{ }\frac{1}{ \mathcal {N}_{1}}+m \mathcal {N}_{5}]\\ & < &\Re _{1} = \|\Lambda\|_{1}, \end{array} |
and
\begin{array}{l} _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}}\widetilde{\Lambda}(t)& = &\sum\limits_{i = 1}^{m_{3}}\pi_{i} (_{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {T}\Lambda_{i})(t)\\ & = &\sum\limits_{i = 1}^{m_{3}}\pi_{i}[\int_{0}^{1}\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \Lambda_{i}({\upsilon}))d{\upsilon}\\ &&+\sum\limits_{i = 1}^{m}\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}(\Lambda_{i}(t_{i}))]\\ & < &\|\Lambda_{i}\|_{1}(\widetilde{\lambda}-\varepsilon_{1})[{ }\frac{1}{ \mathcal {N}_{3}}+m \mathcal {N}_{7}]\\ &\leq&(\Re _{1}+\epsilon)(\widetilde{\lambda}-\varepsilon_{1})[{ }\frac{1}{ \mathcal {N}_{3}}+m \mathcal {N}_{7}]\\ & < &\Re _{1} = \|\Lambda\|_{1}. \end{array} |
Hence, \|\widetilde{\Lambda}\|_{1} < \|\Lambda\|_{1} , for all \widetilde{\Lambda} \in \mathbb{T}\Lambda and all \Lambda \in P with \|\Lambda\|_{1} = \Re _{1} . By Lemma 2.8 and 2.9, we get
\begin{equation} \ i(\mathcal{T}, \mathcal{P}\cap\partial B_{\Re _{1}}, \mathcal{P}) = 1. \end{equation} | (3.16) |
Together with (3.15), we have
\begin{equation} i(\mathcal{T}, \mathcal{P}\cap(B_{\Re _{1}}\backslash \overline{B}_{{\mathfrak{r}}_{1}}), \mathcal{P} ) = 1-0 = 1. \end{equation} | (3.17) |
Hence, BVP (1.1) admits at least one positive solution.
Theorem 3.2. Assume that (H1)–(H4), (H7) and (H8) hold. In addition, suppose that the following condition is satisfied.
(H9) There exist R > 0 such that \digamma^{R} < { }\frac{ \mathcal {N}_{1}}{2} and \sum\limits_{k = 1}^{m}\Phi_{{\kappa}}^{R} < { }\frac{1}{2 \mathcal {N}_{5}} , where
\Phi_{{\kappa}}^{R} : = sup_{\ 0\leq\|\Lambda\|\leq \frac{6R}{5}}\{{ }\frac{\Phi_{{\kappa}}(\Lambda)}{R}\}, \ \digamma^{R} : = sup_{t\in[0, 1], \ 0\leq\|\Lambda\|\leq \frac{6R}{5}}\{{ }\frac{\digamma(t, \Lambda)}{R}\}. |
Then, BVP (1.1) admits at least two positive solutions.
Proof. We will prove that \mathcal{T} has at least two positive fixed points.
First, by the condition (H7), one can see that there exist {\mathfrak{r}}_{2} , \widetilde{\varepsilon}_{2}\in (0, \nu) . Moreover, {\mathfrak{r}}_{2} , \widetilde{\varepsilon}_{2} satisfy
\digamma(t, \Lambda) < (\nu-\widetilde{\varepsilon}_{2})\Lambda, \ \Phi_{{\kappa}}(\Lambda) < (\nu-\widetilde{\varepsilon}_{2})\Lambda, \ t\in[0, 1], \ \Lambda\in[0, { }\frac{6}{5}{\mathfrak{r}}_{2}]. |
We claim that
\begin{equation} \mu \Lambda\notin \mathbb{T}\Lambda, \ \forall \Lambda\in \mathcal{P}\cap \partial B_{{\mathfrak{r}}_{2}}, \end{equation} | (3.18) |
for \mu\geq1. In fact, on the contrary, if there exist \Lambda\in \mathcal{P}\cap \partial B_{{\mathfrak{r}}_{2}} , \mu\geq 1 such that \mu \Lambda(t) = \mathcal{T}\widetilde{\Lambda}(t) for some \widetilde{\Lambda}\in \overline{B}_{\epsilon}(\Lambda)\cap P, \ i.e.,
\begin{array}{l} \mu \Lambda(t)& = &\int_{0}^{1} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \widetilde{\Lambda} ({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}(\widetilde{\Lambda}(t_{i}))\\ & < &(\nu-\widetilde{\varepsilon}_{2})(\|\Lambda\|_{1}+\epsilon)[({ }\frac{1}{ \mathcal {N}_{1}} +m\mathcal{N}_{5}]\\ & < &{\mathfrak{r}}_{2}. \end{array} |
Then,
\begin{array}{l} \mu (_{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}}\Lambda(t))& = &\int_{0}^{1}\ _{t}^{C} \mathcal {D}^{\Re -1}_{0^{+}} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma({\upsilon}, \widetilde{\Lambda}({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m}\ _{t}^{C} \mathcal {D} ^{\Re -1}_{0^{+}} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}(\widetilde{\Lambda}(t_{i}))\\ & < &(\nu-\widetilde{\varepsilon}_{2})(\|\Lambda\|_{1}+\epsilon)[{ }\frac{1}{ \mathcal {N}_{3}} +m \mathcal {N}_{7}]\\ &\leq&(\nu-\widetilde{\varepsilon}_{2})(\|\Lambda\|_{1}+\epsilon)[({ }\frac{1}{ \mathcal {N}_{1}} +m \mathcal {N}_{5}]\\ & < &{\mathfrak{r}}_{2}. \end{array} |
Over t\in [0, 1] , we obtain
\begin{equation} \mu\|\Lambda\|_{1} = \mu {\mathfrak{r}}_{2} < {\mathfrak{r}}_{2}, \end{equation} | (3.19) |
by taking the supremum, which is a contradiction.
Then, to prove \mu \Lambda \notin co(T(B_{\widetilde{\varepsilon}}(\Lambda) \cap \mathcal{P})) , we consider two cases: \mu = 1 and \mu > 1 . If \mu = 1 , we obtain by the reasonings done above that \Lambda \neq \mathcal {T}\Lambda . This together with condition {\Lambda} \cap \mathbb{T}\Lambda \subset \{ \mathcal {T}\Lambda\} implies \Lambda\notin \mathbb{T}\Lambda . If \mu > 1 , by inequality (3.19), it is a contradiction.
Next, the condition (H8) means that there exist \widetilde{\varepsilon}_{3} > 0 , \mathcal{R} > r_{2} . They satisfy
\digamma(t, \Lambda) > (\widetilde{\nu}+\widetilde{\varepsilon}_{3})\Lambda, \ \Phi_{{\kappa}}(\Lambda) > (\widetilde{\nu}+\widetilde{\varepsilon}_{3})\Lambda, \ t\in[0, 1], \ \Lambda\geq { }\frac{4}{5}\mathcal{R}. |
Choosing \Re _{2} > max\{{\mathfrak{r}}_{1}, \ { }\frac{4\mathcal{R}}{5\mathfrak{d}(s)}\} , for any \Lambda\in \partial \mathcal {P}_{\Re _{2}} , we have
\Lambda(t)\geq \mathfrak{d} \|\Lambda\|_{1} = \mathfrak{d}(s) \Re _{2} > { }\frac{4}{5}\mathcal{R}. |
We claim that
\Lambda\notin \mathbb{T}\Lambda+\mu e, \ e(t)\equiv 1, \ t\in[0, 1], |
for all \Lambda\in \mathcal{P}\cap \partial B_{\Re _{2}} and \mu \geq 0 .
In fact, on the contrary, suppose that there exist \Lambda\in P\cap \partial B_{\Re _{2}} , \mu\geq 0 such that \Lambda = \mathcal{T}\widetilde{\Lambda}+\mu e for some {\widetilde{\Lambda}}\in \overline{B}_{\epsilon}(\Lambda)\cap \mathcal{P}, \ i.e.,
\begin{array}{l} \Lambda(t)& = &\int_{0}^{1} \mathcal {H}_{1}(t, {\upsilon}) \mathcal {E}({\upsilon})\digamma ({\upsilon}, {\widetilde{\Lambda}}({\upsilon}))d{\upsilon}+\sum\limits_{i = 1}^{m} \mathcal {H}_{2}(t, t_{i}) \Phi_{i}({\widetilde{\Lambda}}(t_{i}))+\mu\\ &\geq&(\Re _{2}-\epsilon)\mathfrak{d}({\upsilon}) (\widetilde{\nu}+\widetilde{\varepsilon}_{3}) [{ }\frac{1}{ \mathcal {N}_{2}}+m \mathcal {N}_{6}]+\mu\\ & > &\Re _{2}+\mu. \end{array} |
This together with the definition of \|\cdot\|_{1} guarantees that
\begin{equation} \Re _{2} = \|\Lambda\|_{1}\geq max_{ t\in\ [0, 1]}\Lambda(t) > \Re _{2}+\mu, \end{equation} | (3.20) |
which is a contradiction for \mu \geq 0 .
For p \in { \mathbb{N} } , one can see that \Lambda \neq \sum\limits_{i = 1}^{p}\pi_{i}T{\widetilde{\Lambda}}_{i}+\mu e(\mu\geq0) for \pi_{i}\in[0, 1](i = 1, \ \cdots, \ p) and v_{i}\in B_{\widetilde{\varepsilon}}(\Lambda) \cap P , where \sum\limits_{i = 1}^{p}\pi_{i} = 1 . Hence, \Lambda \notin co(\mathcal{T}(B_{\varepsilon}(\Lambda) \cap \mathcal{P}))+\mu e(\mu\geq0).
Now we are in a position to prove that \Lambda \notin \mathbb{T}\Lambda+\mu e . If \mu = 0 , we obtain by the reasonings done above that \Lambda \neq \mathcal {T}\Lambda .This together with condition {\Lambda} \cap \mathbb{T}\Lambda \subset \{ \mathcal {T}\Lambda\} implies \Lambda\notin \mathbb{T}\Lambda . If \mu > 0 , in view of inequality (3.20), it is a contradiction.
By Lemma 2.8, one can get that i(\mathcal{T}, \ \mathcal{P}\cap \partial B_{{\mathfrak{r}}_{2}}, \ \mathcal{P}) = 1 and i(\mathcal{T}, \ \mathcal{P}\cap \partial B_{\Re _{2}}, \ \mathcal{P}) = 0 . Hence,
\begin{equation} i(\mathcal{T}, \ \mathcal{P}\cap(B_{\Re _{2}}\backslash{\overline{B}}_{{\mathfrak{r}}_{2}}, \ \mathcal{P}) = 0-1 = -1. \end{equation} | (3.21) |
Third, (H9) implies that there exist \Re _{3} > \Re _{2} and \epsilon\in[0, { }\frac{{\mathfrak{r}}_{2}}{5}] such that \digamma^{\Re _{3}} < { }\frac{ \mathcal {N}_{1}}{2} and \sum\limits\limits_{k = 1}^{m}\Phi_{{\kappa}}^{\Re _{3}} < { }\frac{1}{2 \mathcal {N}_{5}} .
Similar to the process above, there exist \Re _{3} > \Re _{2} such that
i(\mathcal{T}, \ \mathcal{P}\cap \partial B_{\Re _{3}}, \mathcal{ P} ) = 1. |
Hence,
i(\mathcal{T}, \ \mathcal{P}\cap(B_{R_{3}}\backslash{\overline{B}}_{\Re _{2}}, \mathcal{P}) = 1-0 = 1. |
Together with (3.21), BVP (1.1) admits at least two positive solutions in \mathcal{P}\cap(B_{\overline{\Re }_{2}}\backslash{\overline{B}}_{{\mathfrak{r}}_{2}}) and \mathcal{P}\cap(B_{\overline{\Re }_{3}}\backslash{\overline{B}}_{\Re _{2}}), respectively.
Example 4.1. Consider the following BVP
\begin{equation} \hskip 3mm\left\{ \begin{array}{lll} _{t}^{C} \mathcal {D}^{1.5}_{0^{+}}\Lambda(t) = \digamma(t, \Lambda), \ a.e.\ t\in[0, 1], \\ \triangle \Lambda|_{t = t_{1}} = \Phi_{1}(\Lambda(t_{1})), \\ \triangle \Lambda'|_{t = t_{1}} = 0, \\ 3 \Lambda(0)- \Lambda(1) = \int_{0}^{1}\frac{1}{2}\Lambda({\upsilon})d{\upsilon}, \\ 3 \Lambda'(0)- \Lambda'(1) = \int_{0}^{1}\Lambda({\upsilon})d{\upsilon}, \end{array}\right. \end{equation} | (4.1) |
where 0 < t_{1} < 1, \Phi_{1}(\Lambda) = { }\frac{\Lambda^{2}}{10^{3}} and
\digamma(t, \Lambda) = \begin{cases} { }\frac{[\Gamma(2.5)]^{2}}{4}{ }\frac{\Lambda^{2}}{10^{3}}[\cos^{2}({ }\frac{\Gamma(2.5)}{2t^{1.5}-\Gamma(2.5)\Lambda})+1], \ \Lambda\neq { }\frac{2t^{1.5}}{\Gamma(2.5)}, \ 0\leq t\leq1;\\ { }\frac{t^{3}}{500}, \ \Lambda = { }\frac{2t^{1.5}}{\Gamma(2.5)}, \ 0\leq t\leq1. \end{cases} |
Conclusion: BVP (4.1) has at least two positive solutions.
Proof. First, \digamma satisfies condition (H2) by it's expression. On the other hand, the function \Lambda\rightarrow \digamma(t, \Lambda) is continuous on
{ \mathbb{R} }^{+}\setminus\bigcup\limits_{t\in Q} \{\hbar_{n}(t)\}, |
where for each n \in \mbox{ $\mathbb{Z}$ } \setminus \{0\} and a.e. t \in Q . The curves \hbar_{n}(t) = { }\frac{2t^{1.5}}{\Gamma(2.5)}-n^{-1} and \hbar_{0}(t) = { }\frac{2t^{1.5}}{\Gamma(2.5)} are admissible discontinuity curves satisfying
1 = \ _{t}^{C} \mathcal {D}^{1.5}_{0^{+}}\hbar_{n}(t)-1 > \digamma(t, z) |
where z\in [\hbar_{n}(t)-1, \hbar_{n}(t)+1], \ t\in[0, 1].
By Lemma 2.3, one can obtain that \mathfrak{A}_{1} = { }\frac{1}{2}, \ \mathfrak{A}_{2} = 1 , \mathfrak{P}_{1} = \mathfrak{Q}_{1} = { }\frac{1}{4} , \mathfrak{P}_{2} = \mathfrak{Q}_{2} = { }\frac{1}{2} , \Gamma_{1} = { }\frac{1}{8} > 0 , \varphi_{1}(t) = 2t+2 , \varphi_{2}(t) = 3t+{ }\frac{5}{2} ,
\aleph(t, {\upsilon}) = \begin{cases} { }\frac{(t-{\upsilon})^{0.5}}{\Gamma(1.5)}+{ }\frac{(1-{\upsilon})^{0.5}}{2\Gamma(1.5)}+{ }\frac{(1+2t)(1-{\upsilon})^{-0.5}}{4\Gamma(0.5)}, \ 0\leq {\upsilon}\leq t\leq1;\\ { }\frac{(1-{\upsilon})^{0.5}}{2\Gamma(1.5)}+{ }\frac{(1+2t)(1-{\upsilon})^{-0.5}}{4\Gamma(0.5)}, \ 0\leq t\leq {\upsilon}\leq 1, \end{cases} |
\begin{equation} \mathcal {H}_{2}(t, t_{i}) = \left\{ \begin{aligned} { }\frac{1}{2}+{ }\frac{1}{2}(4t+{ }\frac{7}{2}), \ 0\leq t\leq t_{i}\leq1;\\ { }\frac{3}{2}+{ }\frac{3}{2}(4t+{ }\frac{7}{2}), \ 0\leq t_{i} < t\leq 1. \end{aligned} \right. \end{equation} | (4.2) |
Thus, by calculation, we can get that (\mathcal {N}_{1})^{-1}\approx10.458 , (\mathcal {N}_{2})^{-1}\approx4.375 , (\mathcal {N}_{3})^{-1}\approx5.333 , (\mathcal {N}_{4})^{-1}\approx4.333 , \mathcal {N}_{5} = { }\frac{51}{4} , \mathcal {N}_{6} = { }\frac{9}{4} , \mathcal {N}_{7} = 6 , \mathcal {N}_{8} = 2 . Choosing \nu = 0.03 and \widetilde{\nu} = 2 , which satisfies 5\nu({ }\frac{1}{ \mathcal {N}_{1}}+mN_{5})\leq 4 and 3\mathfrak{d} \widetilde{\nu}({ }\frac{1}{ \mathcal {N}_{2}}+mN_{6})\geq 4 .
Therefore,
\lim\limits_{\Lambda\rightarrow 0^{+}}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} = 0 < \nu, \ \lim\limits_{\Lambda\rightarrow 0^{+}}\sup \limits_{t\in [0, 1]}{ }\frac{\digamma(t, \Lambda)}{\Lambda} = 0 < \nu. |
\lim\limits_{\Lambda\rightarrow +\infty}{ }\frac {\Phi_{{\kappa}}(\Lambda)}{\Lambda} = +\infty > \widetilde{\nu}, \ \lim\limits_{\Lambda\rightarrow +\infty}\inf \limits_{t\in [0, 1]}{ }\frac {\digamma(t, \Lambda)}{\Lambda} = +\infty > \widetilde{\nu}. |
Moreover, we have (\mathcal {N}_{1})^{-1}\approx10.458 , \mathcal {N}_{5} = { }\frac{51}{4} and let R_{3} = 10 . Then, (H9) is satisfied.
Hence, all conditions in Theorem 3.4 are satisfied. The proof is completed.
In this work, we studies the existence of positive and multiple positive solutions for a class of BVPs of fractional discontinuous differential equations with impulse effects. The main results are obtained by means of the multivalued analysis and Krasnoselskii's fixed point theorem for discontinuous operators on cones.
For our subsequent work, the following issues will continue to be focused on:
(i) The system is studied on this topic more extensive and complicated. Therefore, it is valuable to investigate FDEs with generalized derivatives or hybrid FDEs with delay.
(ii) With the development of the theoretical study on FDEs, the application area of FDEs with generalized derivatives in reality needs to be investigated in depth.
The authors are thankful to the editor and anonymous referees for their valuable comments and suggestions. This research was funded by NNSF of P.R. China (12271310), Natural Science Foundation of Shandong Province (ZR2020MA007), and Doctoral Research Funds of Shandong Management University(SDMUD202010), QiHang Research Project Funds of Shandong Management University(QH2020Z02).
The authors declare that there are no conflicts of interest.
[1] |
N. A. F. Zamrisham, A. M. Wahab, A. Zainal, D. Karadag, D. Bhutada, S. Suhartini, et al., State of the art in anaerobic treatment of landfill leachate: A review on integrated system, additive substances, and machine learning application, Water, 15 (2023), 1303. https://doi.org/10.3390/w15071303 doi: 10.3390/w15071303
![]() |
[2] |
K. Waszkielis, I. Bialobrzewski, K. Bulkowska, Application of anaerobic digestion model No.1 for simulating fermentation of maize silage, pig manure, cattle manure and digestate in the full-scale biogas plant, Fuel, 317 (2022), 123491. https://doi.org/10.1016/j.fuel.2022.123491 doi: 10.1016/j.fuel.2022.123491
![]() |
[3] |
S. Kusch, H. Oechsner, T. Jungbluth, Effect of various leachate recirculation strategies on batch anaerobic digestion of solid substrates, Int. J. Environ. Waste Manag., 9 (2012), 69–88. https://doi.org/10.1504/IJEWM.2012.044161 doi: 10.1504/IJEWM.2012.044161
![]() |
[4] |
P. J. He, X. Qu, L. M. Shao, G. J. Li, D. J. Lee, Leachate pretreatment for enhancing organic matter conversion in landfill bioreactor, J. Hazard. Mater., 142 (2007), 288–296. https://doi.org/10.1016/j.jhazmat.2006.08.017 doi: 10.1016/j.jhazmat.2006.08.017
![]() |
[5] |
D. R. Reinhart, B. A. Al-Yousfi, The impact of leachate recirculation on municipal solid waste landfill operating characteristics, Waste Manag. Res., 14 (1996), 337–346. https://doi.org/10.1006/wmre.1996.0035 doi: 10.1006/wmre.1996.0035
![]() |
[6] |
H. Benbelkacem, R. Bayard, A. Abdelhay, Y. Zhang, R. Gourdon, Effect of leachate injection modes on municipal solid waste degradation in anaerobic bioreactor, Bioresource Technol., 101 (2010), 5206–5212. https://doi.org/10.1016/j.biortech.2010.02.049 doi: 10.1016/j.biortech.2010.02.049
![]() |
[7] |
L. Liu, H. Xiong, J. Ma, S. Ge, X. Yu, G. Zeng, Leachate recirculation for enhancing methane generation within field site in China, J. Chem., 2018, (2018), 9056561. https://doi.org/10.1155/2018/9056561 doi: 10.1155/2018/9056561
![]() |
[8] |
L. Luo, S. Xu, J. Liang, J. Zhao, J. W. C. Wong, Mechanistic study of the effect of leachate recirculation ratios on the carboxylic acid productions during a two-phase food waste anaerobic digestion, Chem. Eng. J., 453 (2023), 139800. https://doi.org/10.1016/j.cej.2022.139800 doi: 10.1016/j.cej.2022.139800
![]() |
[9] | IWA Task Group for Mathematical Modelling of Anaerobic Digestion Processes, Anaerobic digestion No.1 (ADM1), London, UK: IWA publishing, 2005. https://doi.org/10.2166/9781780403052 |
[10] |
D. J. Batstone, J. Keller, I. Angelidaki, S. V. Kalyuzhnyi, S. G. Pavlostathis, A. Rozzi, et al., The IWA anaerobic digestion model No 1 (ADM1), Water Sci. Technol., 45 (2002), 65–73. https://doi.org/10.2166/wst.2002.0292 doi: 10.2166/wst.2002.0292
![]() |
[11] |
X. Zhao, L. Li, D. Wu, T. Xiao, Y. Ma, X. Peng, Modified anaerobic digestion model No. 1 for modeling methane production from food waste in batch and semi-continuous anaerobic digestions, Bioresoure Technol., 271 (2019), 109–117. https://doi.org/10.1016/j.biortech.2018.09.091 doi: 10.1016/j.biortech.2018.09.091
![]() |
[12] |
A. Bornhoft, R. Hanke-Rauschenbach, K. Sundmacher, Steady-state analysis of the anaerobic digestion model No.1 (ADM1), Nonlinear Dyn., 73 (2013), 535–549. https://doi.org/10.1007/s11071-013-0807-x doi: 10.1007/s11071-013-0807-x
![]() |
[13] |
M. J. Wade, R. W. Pattinson, N. G. Parker, J. Dolfing, Emergent behaviour in a chlorophenol35 mineralising three-tiered microbial 'food web', J. Theor. Biol., 389 (2016), 171–186. https://doi.org/10.1016/j.jtbi.2015.10.032 doi: 10.1016/j.jtbi.2015.10.032
![]() |
[14] |
A. A. Alsolami, M. El Hajji, Mathematical analysis of a bacterial competition in a continuous reactor in the presence of a virus, Mathematics, 11 (2023), 883. https://doi.org/10.3390/math11040883 doi: 10.3390/math11040883
![]() |
[15] |
A. H. Albargi, M. El Hajji, Bacterial competition in the presence of a virus in a chemostat, Mathematics, 11 (2023), 3530. https://doi.org/10.3390/math11163530 doi: 10.3390/math11163530
![]() |
[16] |
G. Lyberatos, I. V. Skiadas, Modelling of anaerobic digestion–A review, Glob. Nest J., 1 (1999), 63–76. https://doi.org/10.30955/gnj.000112 doi: 10.30955/gnj.000112
![]() |
[17] |
M. Weedermann, G. Seo, G. Wolkowicz, Mathematical model of anaerobic digestion in a chemostat: Effects of syntrophy and inhibition, J. Biol. Dyn., 7 (2013), 59–85. https://doi.org/10.1080/17513758.2012.755573 doi: 10.1080/17513758.2012.755573
![]() |
[18] |
S. Sobieszek, M. J. Wade, G. S. K. Wolkowicz, Rich dynamics of a three-tiered anaerobic food-web in a chemostat with multiple substrate inflow, Math. Biosci. Eng., 17 (2020), 7045–7073. https://doi.org/10.3934/mbe.2020363 doi: 10.3934/mbe.2020363
![]() |
[19] |
T. Bayen, G. Pedro, On the steady state optimization of the biogas production in a two-stage anaerobic digestion model, J. Math. Biol., 78 (2019), 1067–1087. https://doi.org/10.1007/s00285-018-1301-3 doi: 10.1007/s00285-018-1301-3
![]() |
[20] | M. El Hajji, N. Chorfi, M. Jleli, Mathematical modelling and analysis for a three-tiered microbial food web in a chemostat, Electron. J. Differ. Equ., 2017 (2017), 1–13. |
[21] |
M. Bisi, M. Groppi, G. Martaló, R. Travaglini, Optimal control of leachate recirculation for anaerobic processes in landfills, Discrete Cont. Dyn. Syst.-B, 26 (2021), 2957–2976. https://doi.org/10.3934/dcdsb.2020215 doi: 10.3934/dcdsb.2020215
![]() |
[22] | O. Laraj, N. El Khattabi, A. Rapaport, Mathematical model of anaerobic digestion with leachate recirculation, hal-03714305f. |
[23] |
M. El Hajji, F. Mazenc, J. Harmand, A mathematical study of a syntrophic relationship of a model of anaerobic digestion process, Math. Biosci. Eng., 7 (2010), 641–656. https://doi.org/10.3934/mbe.2010.7.641 doi: 10.3934/mbe.2010.7.641
![]() |
[24] |
T. Sari, M. El Hajji, J. Harmand, The mathematical analysis of a syntrophic relationship between two microbial species in a chemostat, Math. Biosci. Eng., 9 (2012), 627–645. https://doi.org/10.3934/mbe.2012.9.627 doi: 10.3934/mbe.2012.9.627
![]() |
[25] |
A. Xu, J. Dolfing, T. Curtis, G. Montague, E. Martin, Maintenance affects the stability of a two-tiered microbial 'food chain'? J. Theor. Biol., 276 (2011), 35–41. https://doi.org/10.1016/j.jtbi.2011.01.026 doi: 10.1016/j.jtbi.2011.01.026
![]() |
[26] |
T. Sari, J. Harmand, A model of a syntrophic relationship between two microbial species in a chemostat including maintenance, Math. Biosci., 275 (2016), 1–9. https://doi.org/10.1016/j.mbs.2016.02.008 doi: 10.1016/j.mbs.2016.02.008
![]() |
[27] |
Y. Daoud, N. Abdellatif, T. Sari, J. Harmand, Steady state analysis of a syntrophic model: The effect of a new input substrate concentration, Math. Model. Nat. Phenom., 13 (2018), 31. https://doi.org/10.1051/mmnp/2018037 doi: 10.1051/mmnp/2018037
![]() |
[28] |
R. Fekih-Salem, Y. Daoud, N. Abdellatif, T. Sari, A mathematical model of anaerobic digestion with syntrophic relationship, substrate inhibition and distinct removal rates, SIAM J. Appl. Dyn. Syst., 20 (2021), 1621–1654. https://doi.org/10.1137/20M1376480 doi: 10.1137/20M1376480
![]() |
[29] |
A. H. Albargi, M. El Hajji, Mathematical analysis of a two-tiered microbial food-web model for the anaerobic digestion process, Math. Biosci. Eng., 20 (2023), 6591–6611. https://doi.org/10.3934/mbe.2023283 doi: 10.3934/mbe.2023283
![]() |
[30] |
R. Saidi, P. P. Liebgott, H. Gannoun, L. B. Gaida, B. Miladi, M. Hamdi, et al., Biohydrogen production from hyperthermophilic anaerobic digestion of fruit and vegetable wastes in seawater: Simplification of the culture medium of thermotoga maritima, Waste Manage., 71 (2018), 474–484. https://doi.org/10.1016/j.wasman.2017.09.042 doi: 10.1016/j.wasman.2017.09.042
![]() |
[31] |
M. El Hajji, How can inter-specific interferences explain coexistence or confirm the competitive exclusion principle in a chemostat? Int. J. Biomath., 11 (2018), 1850111. https://doi.org/10.1142/S1793524518501115 doi: 10.1142/S1793524518501115
![]() |
[32] | H. L. Smith, P. Waltman, The theory of the chemostat: Dynamics of microbial competition, Cambridge University Press, 1995. https://doi.org/10.1017/CBO9780511530043 |
[33] |
H. R. Thieme, Convergence results and a Poincaré-Bendixson trichotomy for asymptotically autonomous differential equations, J. Math. Biol., 30 (1992), 755–763. https://doi.org/10.1007/BF00173267 doi: 10.1007/BF00173267
![]() |
[34] |
H. R. Thieme, Asymptotically autonomous differential equations in the plane, Rocky Mountain J. Math., 24 (1993), 351–380. https://doi.org/10.1216/rmjm/1181072470 doi: 10.1216/rmjm/1181072470
![]() |
[35] |
M. El Hajji, Periodic solutions for chikungunya virus dynamics in a seasonal environment with a general incidence rate, AIMS Mathematics, 8 (2023), 24888–24913. https://doi.org/10.3934/math.20231269 doi: 10.3934/math.20231269
![]() |
[36] |
G. Butler, H. I. Freedman, P. Waltman, Uniformly persistent systems, Proc. Amer. Math. Soc., 96 (1986), 425–429. https://doi.org/10.1090/S0002-9939-1986-0822433-4 doi: 10.1090/S0002-9939-1986-0822433-4
![]() |
[37] | W. Fleming, R. Rishel, Deterministic and stochastic optimal control, New York: Springer Verlag, 1975. https://doi.org/10.1007/978-1-4612-6380-7 |
[38] | S. Lenhart, J. T. Workman, Optimal control applied to biological models, Chapman and Hall/CRC, 2007. https://doi.org/10.1201/9781420011418 |
[39] | L. S. Pontryagin, Mathematical theory of optimal processes, Routledge, 1987. https://doi.org/10.1201/9780203749319 |
[40] | J. Monod, Croissance des populations bactériennes en fonction de la concentration de l'aliment hydrocarboné, C. R. Acad. Sci., 212 (1941), 771–773. |
[41] |
J. R. Lobry, J. P. Flandrois, G. Carret, A. Pave, Monod's bacterial growth model revisited, Bull. Math. Biol., 54 (1992), 117–122. https://doi.org/10.1007/BF02458623 doi: 10.1007/BF02458623
![]() |
[42] |
M. El Hajji, Modelling and optimal control for Chikungunya disease, Theory Biosci., 140 (2021), 27–44. https://doi.org/10.1007/s12064-020-00324-4 doi: 10.1007/s12064-020-00324-4
![]() |
[43] |
M. El Hajji, A. Zaghdani, S. Sayari, Mathematical analysis and optimal control for Chikungunya virus with two routes of infection with nonlinear incidence rate, Int. J. Biomath., 15 (2022), 2150088. https://doi.org/10.1142/S1793524521500881 doi: 10.1142/S1793524521500881
![]() |
[44] |
M. El Hajji, S. Sayari, A. Zaghdani, Mathematical analysis of an SIR epidemic model in a continuous reactor–deterministic and probabilistic approaches, J. Korean Math. Soc., 58 (2021), 45–67. https://doi.org/10.4134/JKMS.j190788 doi: 10.4134/JKMS.j190788
![]() |
1. | Nauman Raza, Adil Jhangeer, Zeeshan Amjad, Beenish Rani, Dumitru Baleanu, Exploring soliton dynamics and wave interactions in an extended Kadomtsev-Petviashvili-Boussinesq equation, 2025, 16, 20904479, 103395, 10.1016/j.asej.2025.103395 |