Measure differential inclusions  between continuous and discrete
 Mieczysław Cichoń^{1} and
 Bianca R. Satco^{2}Email author
https://doi.org/10.1186/16871847201456
© Cichoń and Satco; licensee Springer. 2014
Received: 17 October 2013
Accepted: 20 January 2014
Published: 4 February 2014
Abstract
The paper is devoted to the study of the measuredriven differential inclusions $dx(t)\in G(t,x(t))\phantom{\rule{0.2em}{0ex}}d\mu (t)$, $x(0)={x}_{0}$ for arbitrary finite Borel measure μ. This type of results allows one to treat in a similar manner differential and difference inclusions, as well as impulsive problems and therefore to study the evolution of hybrid systems with very complex (including Zeno) behavior. Our method is based on viewing the Borel measures as LebesgueStieltjes measures. We thus obtain, under very general assumptions, the existence of regulated or bounded variation solutions of the considered problem and we indicate some advantages of our approach.
MSC:49N25, 34A60, 93C30, 49J53, 37N35, 34A37.
Keywords
1 Introduction
where $G:[0,1]\times {\mathbb{R}}^{d}\to \mathcal{P}({\mathbb{R}}^{d})$ is a closed convexvalued multifunction and μ is a positive regular Borel measure. This kind of problems covers some wellknown cases like usual differential inclusions (when μ is the Lebesgue measure), difference inclusions (for discrete measure μ) and some impulsive multivalued problems (in the case where the measure μ can be decomposed as a sum of the Lebesgue measure and a finite sum of Dirac measuressee [1–3]). There are several approaches for the above problems (direct methods or time scale analysis, for instance) but our method, based on LebesgueStieltjes integration, seems to be the most natural.
This kind of results has a long history and is well motivated. A very interesting and wellillustrated course on hybrid inclusions can be found in [4], for instance. Nevertheless, several different approaches, different solutions and many applications for measuredriven equations or inclusions can also be found in the literature. Let us note the paper by Moreau [5]. It is necessary to mention at least some basic papers by Code and Loewen [6], Goebel and Teel [7], Sesekin and Fetisova [8], Silva and Vinter [9], Aubin [1, 2], Ahmed [10], Pereira, Silva and Oliveira [11, 12] and recently by Goncharova and Staritsyn [13], Filippova [14], Lygeros, Quincampoix and Rzeżuchowski [3] and Leinevan de Wouw [15]. Note that in this theory discontinuous functions are usually considered as solutions, which means that we can expect some paradoxes. In particular, different functions can serve as solutions for the same problem in different meanings (cf. [16]). Thus we stress that a crucial aspect of this theory is to fix the definition for the concept of a solution for (1).
We concentrate on two aspects of mentioned papers: we relax the assumptions on μ and on G by imposing some conditions related to the optimal control theory and we reduce the general problem by working with LebesgueStieltjes integral equations and utilizing their methods and results.
It should be also noted that our results lead in a natural way to some existence theorems for differential and difference inclusions or impulsive problems (for particular measures). Moreover, as claimed in [9], measuredriven differential inclusions provide a convenient framework for formulating optimal control problems for both conventional and impulse controls.
Let us point out that in the context of differential equations this approach has been known for many years. To the best of our knowledge the first equation with a measure as a coefficient was considered by Kronig and Penney in 1931 [17] and as an integral problem by Atkinson [18] in 1964  in the context of the RiemannStieltjes integral. The systematic study for measureperturbed problems started in the 1970s. It is necessary to mention some basic papers by Sharma [19], Shendge and Joshi [20] or Dhage and Bellale [21]. The method via integral equations for some differential equations (with the PerronStieltjes integral) were continued in a systematic way by Schwabik, Tvrdý and Vejvoda [22] in 1979; then some cases have been studied by Wyderka [23, 24], see also [25]. There is still a growing number of papers dealing with measure differential equations ([26] or [27], for instance).
To end the introductory section, we remark that in the considered case there are some difficulties. One of these lies in the lack of natural assumptions implying the existence of suitable integrals (namely, for discontinuous functions the RiemannStieltjes integral with respect to bounded variation functions might not be welldefined) and then the question of the chosen definition of the concept of solution. Another problem is how to find (or at least approximate) this solution. For measuredriven differential equations there are some satisfactory answers (cf. [8, 27] or [28, 29] for hybrid systems, for instance). For differential inclusions the situation is more complicated, as will be clarified in what follows. We will also focus on some aspects of this theory, which are related to unification of many multivalued problems (including continuous, discrete, and impulsive systems).
2 Miscellaneous results from measure theory
Unlike in the case of usual differential inclusions, the measure theory and the theory of LebesgueStieltjes integrals form the basic tools of our paper. In order to make the paper selfcontained we recall all necessary results from these theories.
 (i)
ν is said to be absolutely continuous with respect to μ if $\nu (A)=0$ whenever $\mu (A)=0$.
 (ii)
ν and μ are said to be mutually singular if there exists a measurable set A with $\mu (A)=\nu (T\setminus A)=0$.
Recall also of the following notions:
 (iii)
A set $E\in \mathcal{A}$ is an atom of the measure μ if $\mu (E)>0$ and each measurable subset F of E has either $\mu (F)=0$ or $\mu (F)=\mu (E)$.
 (iv)
A measure is called nonatomic (or diffuse, in probability theory) if it has no atoms.
 (v)
We shall say that a measure is purely atomic if every measurable set of positive measure contains an atom.
Two atoms ${E}_{1}$ and ${E}_{2}$ are said to be nonequivalent if $d({E}_{1},{E}_{2})=\mu ({E}_{1}\phantom{\rule{0.2em}{0ex}}\mathrm{\Delta}\phantom{\rule{0.2em}{0ex}}{E}_{2})>0$. In this case $\mu ({E}_{1}\cap {E}_{2})=0$. Any σfinite measure has at most a countable number of pairwise nonequivalent atoms (e.g. [[30], p.55]).
We are interested in using Borel measures to solve the problem announced in the Introduction. The classical Riesz Representation Theorem characterizes the finite regular Borel measures on a compact metrizable space as linear continuous functionals on the space of real continuous functions. This characterization is used by most of the authors studying measuredriven equations, e.g. [9, 23].
We prefer here another approach, based on LebesgueStieltjes integration. First of all, recall ([[33], p.438] or [[34], p.126]) that any finite Borel measure on a Polish space (in particular on the unit interval of the real line) is regular. It was shown that every finite Borel measure on the real line agrees with some LebesgueStieltjes measure restricted to the class of Borel sets. More precisely we have:
Theorem 1 [[34], Theorem 3.21]
Let μ be a Borel measure on ℝ with $\mu (B)<\mathrm{\infty}$ for every bounded Borel set B. Then there exists a nondecreasing, rightcontinuous function $F:\mathbb{R}\to \mathbb{R}$ such that $\mu (B)={\mu}_{F}(B)$ for any Borel set B.
Here ${\mu}_{F}$ denotes the LebesgueStieltjes measure with distribution function F. Moreover, it was shown (see [[35], pp.236238]) that:

The measure is nonatomic if and only if F is continuous.

The measure is absolutely continuous with respect to the Lebesgue measure if and only if F is absolutely continuous.

The measure is nonatomic and singular with respect to the Lebesgue measure if and only if F is a singular function.
Recall that a singular function is a function which is continuous and nondecreasing on a real interval and has the derivative 0 except for a set of zero Lebesgue measure. There exist nonconstant singular functions on the unit interval (e.g. [[34], p.282]), examples of such functions being in general constructed using the Cantor set.
Concerning the atoms of LebesgueStieltjes measures, it can be seen in [[34], p.132] or [[36], 211X] that each atom E contains a singleton $a\in E$ for which ${\mu}_{F}(E)={\mu}_{F}(\{a\})$. Comparing to definition (v) above, this explains why in some references (such as [33]) a measure μ is called purely atomic if there exists a countable set A such that the outer measure of each singleton $\{a\}$, $a\in A$ is strictly positive and the outer measure of the complementary of A is 0. Obviously, if each singleton is measurable, then the measure takes the place of the outer measure in the previous sentence.
Then any LebesgueStieltjes measure ${\mu}_{F}$ (associated with F) may be split into a sum of three measures: discrete, absolutely continuous and singular ones.
As we will prove our results via LebesgueStieltjes measures, it is worthwhile to recall some basic properties of LebesgueStieltjes integrals; they are consequences of Proposition 2.3.16 in [27], where the functions are realvalued and the integral under consideration is the PerronStieltjes one (which is even more general than the LebesgueStieltjes integral). For generalized integral equations, investigated also independently of our motivations, the class of regulated functions plays a major role. Solutions for integral problems involving LebesgueStieltjes or PerronStieltjes integrals should be investigated outside the space of continuous functions or the spaces of functions with bounded variation. It was clarified in [27] that the space of regulated functions is the best choice for the space of solutions.
Since the notion of regulated functions has sometimes different meanings, we need to describe this class of functions.
Definition 2 A function $F:[0,1]\to \mathbb{R}$ is said to be regulated if there exist the limits $F(t+)$ and $F(s)$ for all points $t\in [0,1)$ and $s\in (0,1]$.
It is well known that the set of discontinuities for a regulated function is at most countable, but such a function need not be of bounded variation. Moreover, a function $F:[0,1]\to \mathbb{R}$ is regulated if and only if it is a uniform limit of a sequence of finite step functions. The following property of the indefinite KurzweilStieltjes integral implies that solutions of measure differential equations are regulated functions. This can explain when our solutions are either of bounded variation or regulated.
Proposition 3 [[27], Proposition 2.3.16]
 (i)If F is regulated, then so is the primitive $h:[0,1]\to {\mathbb{R}}^{d}$, $h(t)={\int}_{0}^{t}g(s)\phantom{\rule{0.2em}{0ex}}dF(s)$ and for every $t\in [0,1]$,$h\left({t}^{+}\right)h(t)=g(t)[F\left({t}^{+}\right)F(t)]\phantom{\rule{1em}{0ex}}\mathit{\text{and}}\phantom{\rule{1em}{0ex}}h(t)h\left({t}^{}\right)=g(t)[F(t)F\left({t}^{}\right)].$
 (ii)
If F is of bounded variation and g is bounded, then h is also of bounded variation.
By ${\chi}_{A}$ we will denote the characteristic function of the set $A\subset \mathbb{R}$. We also need some preliminary facts from setvalued analysis.
where B is the unit ball of ${\mathbb{R}}^{d}$. In the obvious way we call a multifunction usc when it is usc at each point ${t}_{0}\in [0,1]$.
3 Main results
is crucial. Indeed, as pointed out in an example in [37], taking the integral on a closed, resp. open interval (which is equivalent to integrating on a closed interval the left limit of the function) leads to completely different solutions.
Let us note that for discontinuous solutions there is always a problem how to define a solution in the points of discontinuity. A very interesting survey on the topic can be found in [16]. We need to remark that distinct definitions of solutions can lead to distinct solutions [38]! The existence and uniqueness of solutions of considered problems depend on the conditions for μ and g. Due to the existence of atoms for the measure μ there is a question about the uniqueness of solutions for a (possibly) discontinuous function g. The explicit scheme $\mathrm{\Delta}x(t)=x(t)x({t}^{})=g(x({t}^{}))$ is a natural choice for physical systems and we will follow this idea. This allows us to fill the gap in this theory. If we compare our result with some earlier ones we need to recall that for purely atomic measure μ the above condition of integrability means that the series ${\sum}_{k}g({t}_{k})\mu \{{t}_{k}\}$ is finite (where ${t}_{k}$ is a set of atoms for μ)  cf. [8, 16], for instance.
Let us present some auxiliary result:
□
We are ready to present our first result for measuredriven differential inclusions (1) for a general class of finite Borel measures. Let us note that the presented theorem is intended to unify and to extend the earlier ones. We not only formulate an existence result, but we also include a method how to find this solution as a limit of some approximations. We refer the reader to [16] for the discussion, some motivations and examples for measuredriven problems.
 (1)
$G(\cdot ,\cdot )$ is product Borel measurable,
 (2)
$G(t,\cdot )$ is usc for every $t\in [0,1]$,
 (3)there exists a μintegrable function $M:[0,1]\to {\mathbb{R}}_{+}$ such that$d(0,G(t,y))\le M(t),\phantom{\rule{1em}{0ex}}\mathrm{\forall}t\in [0,1],y\in {\mathbb{R}}^{d}.$
Then there exists at least one solution for the measuredriven differential problem (1).
Proof Our proof is based on an iteration procedure. More precisely, we construct a sequence of approximate solutions (being regulated functions) which is shown to have a convergent subsequence due to some compactness properties.
So, let ${x}^{0}(t)={x}_{0}$ for $t\in [0,1]$. Suppose then that we have already constructed a regulated (bounded variation (BV)) function ${x}^{n}$ on $[0,1]$ and choose ${x}^{n+1}$ by following a scheme that is described in the sequel.
By our hypotheses on G we ensure that the function G is superpositionally Borel measurable [40]. Since ${x}^{n}$ is regulated (BV), there exists ${x}^{n}({t}^{})$ at every point t. It can be obtained as ${x}^{n}({t}^{})={lim}_{m\to \mathrm{\infty}}{x}^{n}(t{\tau}_{m})$, where ${({\tau}_{m})}_{m}$ is a sequence of positive numbers converging to 0 (such that $t{\tau}_{m}\in [0,1]$). Therefore the function $t\mapsto {x}^{n}({t}^{})$ is measurable as a pointwise limit of a sequence of measurable functions and then the multifunction $t\mapsto G(t,{x}^{n}({t}^{}))$ is Borel measurable too.
As it was presented in the preliminary part of the paper (Theorem 1), the measure μ is, in fact, a LebesgueStieltjes measure with respect to a BV, rightcontinuous function F. Thus the previous integral should be understood in the sense of ${\int}_{0}^{t}{g}^{n}(s)\phantom{\rule{0.2em}{0ex}}d{\mu}_{F}(s)$ i.e. as a LebesgueStieltjes integral. This integral is well defined since the selection ${g}^{n}$ is Borel measurable, F is of bounded variation and, as said before, bounded by $M(t)$. Moreover, by Proposition 3, ${x}^{n+1}$ is a regulated function.
The function F is of bounded variation and rightcontinuous, therefore it has at most countable points of left discontinuity. Let $A=\{{t}_{k}:k\in \mathbb{N}\}$ be the set of its discontinuity points.
has the property that the subsequence of ${({x}^{n})}_{n}$ is pointwise convergent to x.
and it can be seen that it tends to 0 since ${x}^{n}(t)\to x(t)$, ${g}^{n1}(t)\to g(t)$ and $\parallel F(t)F({t}^{})\parallel \le {\parallel F\parallel}_{\mathrm{BV}}<\mathrm{\infty}$.
and so, x is a solution. □
Remark 7 The solutions are, following Proposition 3, regulated. In the particular case where M is bounded, all approximate solutions ${x}^{n}$ and our solution too are, in fact, of bounded variation.
Moreover, when μ is absolutely continuous with respect to the Lebesgue measure we obtain a result related to that in [[45], Theorem 4, p.101]. Our theorem provides the existence of slow solutions for the considered problem in the sense of [[45], Definition 1, p.97].
Under a different boundedness assumption, very natural and well known in Lebesgue integration, we get another existence result.
Theorem 8 Let the finite Borel measure μ on $[0,1]$ and $G:[0,1]\times {\mathbb{R}}^{d}\to {\mathcal{P}}_{cc}({\mathbb{R}}^{d})$ satisfy hypotheses (1), (2) in Theorem 6 and
(3′) there exist a positive function $M\in {L}^{1}([0,1],\mu )$ and a constant $N>0$ such that $G(t,y)\subset [M(t)+N\parallel y\parallel ]B$ for all $t\in [0,1]$ and $y\in {\mathbb{R}}^{d}$.
Then there exists at least one solution for the measuredriven differential problem (1) on some interval $[0,T]\subset [0,1]$.
Proof First, as the map $t\mapsto {\int}_{0}^{t}M(s)\phantom{\rule{0.2em}{0ex}}d\mu (s)$ is regulated, it is bounded on $[0,1]$ by some $M>0$. Also, denoting by $K(t)={\int}_{0}^{t}d\mu (s)$, we get a nondecreasing function. Since 0 is not a point of discontinuity, one can choose $T\in [0,1]$ such that $NK(T)<1$.
The rest of the proof goes as before, and thus the existence of solutions in the considered sense is achieved. □
By applying an appropriate version of Gronwall’s lemma we will be able to prove that, in fact, under the assumptions of the previous theorem, one can find global solutions.
Let us recall the following Gronwalltype result (where ${D}_{\mu}$ denotes the set of all atoms of μ):
Lemma 9 [[46], Lemma 8.5]
Recall that ${\phi}_{0}(t)\le exp{Var}_{[0,t]}\mu $ and the latest is increasing and of bounded variation.
Theorem 11 Let the finite Borel measure μ on $[0,1]$ and $G:[0,1]\times {\mathbb{R}}^{d}\to {\mathcal{P}}_{cc}({\mathbb{R}}^{d})$ satisfy hypotheses in Theorem 8. Then there exists at least one global solution for the measuredriven differential problem (1).
for every $t\in [0,1]$.
 (1)
$\tilde{G}(\cdot ,\cdot )$ is product Borel measurable,
 (2)
$\tilde{G}(t,\cdot )$ is usc for every $t\in [0,1]$,
 (3)there exists a μintegrable function $M(t)+NK$ such that$\tilde{G}(t,y)\subset (M(t)+NK)B,\phantom{\rule{1em}{0ex}}\mathrm{\forall}t\in [0,1],y\in {\mathbb{R}}^{d}.$
Step III. Since on both branches $\tilde{G}(t,y)\subset [M(t)+N\parallel y\parallel ]B$ for all $t\in [0,1]$ and $y\in {\mathbb{R}}^{d}$ we can show, by using Gronwall’s Lemma like at Step I, that any solution obtained at Step II satisfies the inequality $\parallel x(t)\parallel \le K$ and so, it is a solution of the initial value problem (1). □
Remark 12 (i) As it can be seen in our results, the usual assumptions in setvalued analysis are used in a natural way and conduct to existence results for a finite Borel measuredriven differential inclusion. Of course, in the proof, the measuretheory results available for complete measures, such as equivalent definitions of measurability of multifunctions (cf. [[42], Chapter III] or [41]), must be avoided.
(ii) Let us now notice that in the main theorems we replaced the condition that G is (locally) Lipschitz (which was used in most of the previously obtained existence results for measuredriven inclusions) by its upper semicontinuity. Moreover, comparing to [9] (which also considers upper semicontinuous multifunctions), we imposed only the upper semicontinuity with respect to the second argument, along with a jointly measurability condition. Since such a kind of results has many applications in the control theory, it seems to be an important improvement. It is very natural to require this kind of assumptions instead of stronger ones. For differential inclusions this is sufficient for proving upper semicontinuity of the solution mapping and then to find an optimal control (cf. [49] or [[16], Chapter 6], for instance).
The considered in this model dynamical system is a sum of a slowtime velocity belonging to a set $F(x)$ and a fasttime contribution coming from another set $G(x)\phantom{\rule{0.2em}{0ex}}d{\mu}_{s}$, where ${\mu}_{s}$ is a vectorvalued discrete measure.
Our existence results allow to assert that the problem possess solutions in the more general case where both multifunctions can be timedependent and only upper semicontinuous.
In a series of papers of Silva and his collaborators (e.g. [9]) another definition for the solution was considered (going back to [51]). The main idea is to use a reparametrization method for μ and in this way to transform the measuredriven differential inclusions into usual differential inclusions.
In earlier works a kind of limit solutions x was considered (i.e. x is a limit of approximated solutions ${x}_{n}$ for problems driven by measures ${\mu}_{n}$ tending, in some sense, to μ  cf. [52]). More precisely, the measure μ was approximated by measures ${\mu}_{n}$ which are absolutely continuous with respect to the Lebesgue measure and the limit was shown to be independent on the choice of this sequence ${({\mu}_{n})}_{n}$, see [46]. A similar concept (approximable solutions) for particular measures can be found in [8, 16].
It is interesting that these two definitions are equivalent and can be described as follows.
In some particular cases (as, for example, the problem studied in [3]) our Definition 4 of a solution is equivalent to that of a robust solution. Obviously, for a general Borel measure μ the two concepts are distinct.
Our concept of solution does not offer this closure property (as stated in [[9], p.731]), which is essential in some cases (see [51] or [9]), but we consider more general problems and in many situations, for nonrobust systems (see [16, 46, 53]) solutions as in our Definition 4 are also good enough.
Recall that when considering discontinuous solutions, a fixed measuredriven problem can have solution in one sense and not to have solutions in another sense. Furthemore, different functions can be simultaneously solutions for the same problemconsidered in different senses. So, obviously, separate solutions require separate existence theorems.
Until now, we described the problem with an arbitrary Borel measure. One of the possible extensions is to consider for each of the three measures in which our measure can be decomposed $\mu ={\mu}_{ac}+{\mu}_{ns}+{\mu}_{pa}$ (see Section 2) a different set of assumptions. In our main theorem we impose $G\phantom{\rule{0.2em}{0ex}}d\mu ={G}_{1}\phantom{\rule{0.2em}{0ex}}d{\mu}_{ac}+{G}_{2}\phantom{\rule{0.2em}{0ex}}d{\mu}_{ns}+{G}_{3}\phantom{\rule{0.2em}{0ex}}d{\mu}_{pa}$ with $G={G}_{1}={G}_{2}={G}_{3}$, i.e. the assumptions on ${G}_{i}$ ($i=1,2,3$) should be the same. Almost all papers dealing with measureperturbed multivalued problems are devoted to the study of only some particular cases of our problem. This is motivated by direct applications of obtained results or there are some problems in the proposed proofs. Moreover, different kind of solutions are considered (mainly due to different applications or proofs). In our opinion, the general case seems to be interesting, because this allows one to indicate some possible extensions in earlier papers.
 1.
${x}_{ac}(t)={x}_{0}+{\int}_{0}^{t}{g}_{ac}(s)\phantom{\rule{0.2em}{0ex}}d{\mu}_{ac}(s)$ for $t\in [0,1]$ and for some ${\mu}_{ac}$integrable function ${g}_{ac}:[0,1]\to {\mathbb{R}}^{d}$ and ${g}_{ac}(t)\in {G}_{1}(t,x({t}^{}))$ ${\mu}_{ac}$a.e.,
 2.
${x}_{ns}(t)={\int}_{0}^{t}{g}_{ns}(s)\phantom{\rule{0.2em}{0ex}}d{\mu}_{ns}(s)$ for some ${\mu}_{ns}$integrable function ${g}_{ns}:[0,1]\to {\mathbb{R}}^{d}$ and ${g}_{ns}(t)\in {G}_{2}(t,x({t}^{}))$ ${\mu}_{ns}$a.e.,
 3.
${x}_{pa}(t)={\int}_{0}^{t}{g}_{pa}(s)\phantom{\rule{0.2em}{0ex}}d{\mu}_{pa}(s)$ for some ${\mu}_{pa}$integrable function ${g}_{pa}:[0,1]\to {\mathbb{R}}^{d}$ and ${g}_{pa}(t)\in {\tilde{G}}_{3}(t,x({t}^{});{\mu}_{pa}(t))$ ${\mu}_{pa}$a.e.
where A denote a set of atoms for μ and all the above integrals should be finite (convergent).
The theorem given below allows us to distinguish between different assumptions on every part of the measure μ.
 1.
${G}_{1}:[0,1]\times {\mathbb{R}}^{d}\to {\mathcal{P}}_{cc}({\mathbb{R}}^{d})$ is such that ${G}_{1}(\cdot ,\cdot )$ is product Borel measurable, ${G}_{1}(t,\cdot )$ is usc for every $t\in [0,1]$, there exist a positive function ${M}_{1}\in {L}^{1}([0,1],{\mu}_{ac})$ and a constant ${N}_{1}>0$ such that $G(t,y)\subset [{M}_{1}(t)+{N}_{1}\parallel y\parallel ]B$ for all $t\in [0,1]$ and $y\in {\mathbb{R}}^{d}$,
 2.
${G}_{2}:[0,1]\times {\mathbb{R}}^{d}\to {\mathcal{P}}_{cc}({\mathbb{R}}^{d})$ is such that ${G}_{2}(\cdot ,\cdot )$ is product Borel measurable, ${G}_{2}(t,\cdot )$ is usc for every $t\in [0,1]$, there exists a positive function ${M}_{2}\in {L}^{1}([0,1],{\mu}_{ns})$ such that $d(0,G(t,y))\le {M}_{2}(t)$ for all $t\in [0,1]$ and $y\in {\mathbb{R}}^{d}$,
 3.
${G}_{3}$ is such that $S:[0,1]\times {\mathbb{R}}^{d}\times [0,1]\to {\mathcal{P}}_{cc}({\mathbb{R}}^{d})$ has compact values and is bounded by ${M}_{3}$. Moreover the setvalued map $S(t,\cdot ,\alpha ):{\mathbb{R}}^{d}\to {\mathbb{R}}^{d}$ is usc, uniformly in $t,\alpha \in [0,1]$.
Then there exists at least one solution for the measuredriven differential problem (8).
The proof of the above theorem runs like the proof of our main theorem with an appropriate change of the definition of a sequence $({x}_{n})$, so we leave a detailed proof to the reader.
The proposed approach via measuredriven inclusions seems to be interesting, because it allows one to unify separately investigated cases for different multivalued problems. Let us recall that in the cases listed below solutions are treated in the sense of Definition 4. This means that there is no general method for an approximation of such solutions (like in our Definition 14) and from this point of view our results are more applicable.
Corollary 18 [[45], p.98]
Let $Q\subset \mathbb{R}\times {\mathbb{R}}^{d}$ be an open subset containing $(0,{x}_{0})$. Let F be an upper semicontinuous map from Q into the nonempty closed convex subsets of ${\mathbb{R}}^{d}$. We assume that $(t,x)\to m(F(t,x))$ is locally compact. Then there exist $T>0$ and an absolutely continuous function $x(\cdot )$ defined on $[0,T]$, a (slow) solution to the differential inclusion ${x}^{\prime}(t)\in F(t,x(t))$, $x(0)={x}_{0}$.
Here the minimal selection $m(F(t,x))$ of a multifunction F is locally compact in the sense that for each point $(t,x)$ one can find a neighborhood which is mapped into a compact set (see [[45], p.97]).
Corollary 19 [[9], Corollary 4.2]
Then for any positive Borel measure having the Lebesgue decomposition $\mu ={\mu}_{ac}+{\mu}_{pa}$ (i.e. ${\mu}_{ns}\equiv 0$) and arbitrary ${x}_{0}\in {\mathbb{R}}^{n}$ there exists a solution for (8).
For the case of discrete measures let us recall the following result formulated in [56] in the language of dynamic inclusions i.e. inclusions on time scales (cf. also [57]). Here we consider the case $\mathbb{T}=\mathbb{Z}$ and then we have a difference inclusion.
Notice that difference inclusions are also investigated without the context of time scales. A similar result to the one presented above can be found in [[58], Theorem 2.1] in a direct form of difference inclusions. In [59] difference inclusions are used to solve some problems in optimal control theory. In particular, it was proved that any solution for autonomous differential inclusions can be approximated by a sequence of solutions for difference inclusions (the multifunction G is assumed to be bounded and Lipschitz). A brief discussion of other motivations for difference inclusions can be found in [60] (see also the references therein). We refer to [61] for a full survey of difference methods for differential inclusions. Also, the problem for difference inclusions was investigated in the case of impulsive differential inclusions ([62], for instance) and in this setting our approach seems to be natural and does not require separate studies.
Moreover, some results presented for the case of socalled qdifference inclusions could be reformulated in our language, but till now they are only particular cases of Corollary 20.
Declarations
Acknowledgements
The authors are deeply indebted to the anonymous reviewers for their valuable suggestions. This work was supported by a grant of the Romanian National Authority for Scientific Research, CNCSUEFISCDI, project number PNIIRUTE201230336.
Authors’ Affiliations
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