Extremal Solutions and Relaxation Problems for Fractional Differential Inclusions
Abstract
We present the existence of extremal solution and relaxation problem for fractional differential inclusion with initial conditions.
1. Introduction
Differential equations with fractional order have recently proved to be valuable tools in the modeling of many physical phenomena [1–9]. There has also been a significant theoretical development in fractional differential equations in recent years; see the monographs of Kilbas et al. [10], Miller and Ross [11], Podlubny [12], and Samko et al. [13] and the papers of Kilbas and Trujillo [14], Nahušev [15], Podlubny et al. [16], and Yu and Gao [17].
Recently, some basic theory for initial value problems for fractional differential equations and inclusions involving the Riemann-Liouville differential operator was discussed, for example, by Lakshmikantham [18] and Chalco-Cano et al. [19].
Applied problems requiring definitions of fractional derivatives are those that are physically interpretable for initial conditions containing y(0), y′(0), and so forth. The same requirements are true for boundary conditions. Caputo’s fractional derivative satisfies these demands. For more details on the geometric and physical interpretation for fractional derivatives of both Riemann-Liouville and Caputo types, see Podlubny [12].
Fractional calculus has a long history. We refer the reader to [20].
Recently fractional functional differential equations and inclusions and impulsive fractional differential equations and inclusions with standard Riemann-Liouville and Caputo derivatives with differences conditions were studied by Abbas et al. [21, 22], Benchohra et al. [23], Henderson and Ouahab [24, 25], Jiao and Zhou [26], and Ouahab [27–29] and in the references therein.
During the last couple of years, the existence of extremal solutions and relaxation problem for ordinary differential inclusions was studied by many authors, for example, see [30–34] and the references therein.
The paper is organized as follows. We first collect some background material and basic results from multivalued analysis and give some results on fractional calculus in Sections 2 and 3, respectively. Then, we will be concerned with the existence of solution for extremal problem. This is the aim of Section 4. In Section 5, we prove the relaxation problem.
2. Preliminaries
The reader is assumed to be familiar with the theory of multivalued analysis and differential inclusions in Banach spaces, as presented in Aubin et al. [35, 36], Hu and Papageorgiou [37], Kisielewicz [38], and Tolstonogov [32].
Definition 1. A multifunction F : X → 𝒫(Y) is said to be upper semicontinuous at the point x0 ∈ X, if, for every open W⊆Y such that F(x0) ⊂ W, there exists a neighborhood V(x0) of x0 such that F(V(x0)) ⊂ W.
A multifunction is called upper semicontinuous (u.s.c. for short) on X if for each x ∈ X it is u.s.c. at x.
Definition 2. A multifunction F : X → 𝒫(Y) is said to be lower continuous at the point x0 ∈ X, if, for every open W⊆Y such that F(x0)∩W ≠ ∅, there exists a neighborhood V(x0) of x0 with property that F(x)∩W ≠ ∅ for all x ∈ V(x0).
A multifunction is called lower semicontinuous (l.s.c. for short) provided that it is lower semicontinuous at every point x ∈ X.
Lemma 3 (see [39], Lemma 3.2.)Let F : [0, b] → 𝒫(Y) be a measurable multivalued map and u : [a, b] → Y a measurable function. Then for any measurable v : [a, b]→(0, +∞), there exists a measurable selection fv of F such that for a.e. t ∈ [a, b],
Definition 4. A multifunction F : Y → 𝒫(X) is called Hausdorff lower semicontinuous at the point y0 ∈ Y, if for any ϵ > 0 there exists a neighbourhood U(y0) of the point y0 such that
Definition 5. A multifunction F : Y → 𝒫(X) is called Hausdorff upper semicontinuous at the point y0 ∈ Y, if for any ϵ > 0 there exists a neighbourhood U(y0) of the point y0 such that
F is called continuous, if it is Hausdorff lower and upper semicontinuous.
Definition 6. Let X be a Banach space; a subset A ⊂ L1([0, b], X) is decomposable if, for all u, v ∈ A and for every Lebesgue measurable set I ⊂ J, one has
Definition 7. Let F : [0, b] × X → 𝒫(X) be a multivalued map with nonempty compact values. We say that F is of lower semicontinuous type (l.s.c. type) if its associated Nemyts’kiĭ operator ℱ is lower semicontinuous and has nonempty closed and decomposable values.
Next, we state a classical selection theorem due to Bressan and Colombo.
Lemma 8 (see [40].)Let X be a separable metric space and let E be a Banach space. Then every l.s.c. multivalued operator N : X → 𝒫cl(L1([0, b], E)) with closed decomposable values has a continuous selection; that is, there exists a continuous single-valued function f : X → L1([0, b], E) such that f(x) ∈ N(x) for every x ∈ X.
-
F : [0, b] × X → 𝒫(X) is a nonempty compact valued multivalued map such that
- (a)
the mapping (t, y) ↦ F(t, y) is ℒ ⊗ ℬ measurable;
- (b)
the mapping y ↦ F(t, y) is lower semicontinuous for a.e. t ∈ [0, b].
- (a)
Lemma 9 (see, e.g., [41]). Let F : J × X → 𝒫cp(E) be an integrably bounded multivalued map satisfying . Then F is of lower semicontinuous type.
Lemma 10 (see [37].)Let K ⊂ X be a weakly compact subset of X. Then F(K) is relatively weakly compact subset of L1([0, b], X). Moreover if K is convex, then F(K) is weakly compact in L1([0, b], X).
Definition 11. A multifunction F : [0, b] × Y → 𝒫wcpcv(X) possesses the Scorza-Dragoni property (S-D property) if for each ϵ > 0, there exists a closed set Jϵ ⊂ [0, b] whose Lebesgue measure μ(Jϵ) ≤ ϵ and such that F : [0, b]∖Jϵ × Y → X is continuous with respect to the metric dX(·, ·).
Remark 12. It is well known that if the map F : [0, b] × Y → 𝒫wcpcv(X) is continuous with respect to y for almost every t ∈ [0, b] and is measurable with respect to t for every y ∈ Y, then it possesses the S-D property.
In what follows, we present some definitions and properties of extreme points.
Definition 13. Let A be a nonempty subset of a real or complex linear vector space. An extreme point of a convex set A is a point x ∈ A with the property that if x = λy + (1 − λ)z with y, z ∈ A and λ ∈ [0,1], then y = x and/or z = x. ext(A) will denote the set of extreme points of A.
In other words, an extreme point is a point that is not an interior point of any line segment lying entirely in A.
Lemma 14 (see [42].)A nonempty compact set in a locally convex linear topological space has extremal points.
Lemma 15 (see [33].)u ∈ ext (A) if and only if dn(A, u) = 0 for all n ≥ 1.
In accordance with Krein-Milman and Trojansky theorem [43], the set ext(SF) is nonempty and .
Lemma 16 (see [33].)Let F : [0, b] → 𝒫wcpcv(X) be a measurable, integrably bounded map. Then
Theorem 17 (see [33].)Let F : [0, b] × Y → 𝒫wcpcv(X) be a multivalued map that has the S-D property and let it be integrable bounded on compacts from Y. Consider a compact subset K ⊂ C([0, b], X) and define the multivalued map G : K → L1([0, b], X), by
For a background of extreme point of F(t, y(t)) see Dunford-Schwartz [42, Chapter 5, Section 8] and Florenzano and Le Van [44, Chapter 3].
3. Fractional Calculus
Definition 18 (see [13], [45].)The fractional integral of order α > 0 of a function f ∈ L1([a, b], ℝ) is defined by
Definition 19. For a function f given on interval [a, b], the αth Riemann-Liouville fractional-order derivative of f is defined by
We now observe an alternative definition of fractional derivative, originally introduced by Caputo [46, 47] in the late sixties and adopted by Caputo and Mainardi [48] in the framework of the theory of Linear Viscoelasticity (see a review in [4]).
Definition 20. Let f ∈ ACn([a, b]). The Caputo fractional-order derivative of f is defined by
Lemma 21 (see [10].)Let α > 0 and let y ∈ L∞(a, b) or C([a, b]). Then
Lemma 22 (see [10].)Let α > 0 and n = [α] + 1. If y ∈ ACn[a, b] or y ∈ Cn[a, b], then
For further readings and details on fractional calculus, we refer to the books and papers by Kilbas [10], Podlubny [12], Samko [13], and Caputo [46–48].
4. Existence Result
Definition 23. A function y ∈ C([0, b], ℝN) is called mild solution of problem (1) if there exist f ∈ L1(J, ℝN) such that
-
(ℋ1) The function F : J × ℝN → 𝒫cpcv(ℝN) such that
- (a)
for all x ∈ ℝN, the map t ↦ F(t, x) is measurable,
- (b)
for every t ∈ [0, b], the multivalued map x → F(t, x) is Hd continuous
- (a)
-
(ℋ2) There exist p ∈ L1(J, ℝ+) and a continuous nondecreasing function ψ : [0, ∞)→(0, ∞) such that
()with()
Theorem 24. Assume that the conditions (ℋ1)-(ℋ2) and then the problem (2) have at least one solution.
Proof. From (ℋ2) there exists M > 0 such that ∥y∥∞ ≤ M for each y ∈ Sc.
Let
Set
Then
5. The Relaxed Problem
In this section, we examine whether the solutions of the extremal problem are dense in those of the convexified one. Such a result is important in optimal control theory whether the relaxed optimal state can be approximated by original states; the relaxed problems are generally much simpler to build. For the problem for first-order differential inclusions, we refer, for example, to [35, Theorem 2, page 124] or [36, Theorem 10.4.4, page 402]. For the relaxation of extremal problems we see the following recent references [30, 50].
Now we present our main result of this section.
Theorem 25. Let F : [0, b] × ℝN → 𝒫(ℝN) be a multifunction satisfying the following hypotheses.
-
(ℋ3) The function F : [0, b] × ℝN → 𝒫cpcv(ℝN) such that, for all x ∈ ℝN, the map
()is measurable. -
(ℋ4) There exists p ∈ L1(J, ℝ+) such that
()
Proof. By Coviz and Nadlar fixed point theorem, we can easily prove that Sc ≠ ∅, and since F has compact and convex valued, then Sc is compact in C([0, b], ℝN). For more information we see [25, 27–29, 51, 52].
Let y ∈ Sc; then there exists f ∈ SF,y such that
Example 26. Let F : J × ℝN → 𝒫cpcv(ℝN) with
Then (2) is solvable.
Example 27. If, in addition to the conditions on F of Example 26, f1 and f2 are Lipschitz functions, then .
Acknowledgments
This work is partially supported by the Ministerio de Economia y Competitividad, Spain, project MTM2010-15314, and cofinanced by the European Community Fund FEDER.