Abstract
In this article, we study some existence and controllability results for two classes of second order functional differential equations with delay and random effects. To begin, we employ a random fixed point theorem with a stochastic domain to demonstrate the existence of mild random solutions. Next, we prove that our problems are controllable. Finally, an example is given to validate the theory part.
Keywords:
random fixed point; functional differential equation; state-dependent delay; cosine and sine family; mild solution; controllability; finite delay MSC:
34G20; 34K20; 34K30; 93B05
1. Introduction
Throughout the development of emerging control theory, the controllability of differential equation problems has played a major role. It typically indicates that the set of permissible controls may be used to direct a dynamical system from an arbitrary initial state to the intended terminal one. The qualitative properties of control systems have a particular importance in control theory. The controllability of linear and nonlinear systems described by ordinary differential equations in finite-dimensional space has received a great deal of attention. Numerous researchers have expanded the notion to infinite-dimensional systems with bounded operators in Banach spaces, see [,,,]. The authors of [] demonstrated how to transform the controllability problem into a fixed point problem. We suggest the papers [,] for more details. In [,,,], the authors explored a wide range of functional differential equations and inclusions and suggested various controllability results. Dilao et al. [] considered the controllability of a class of integrodifferential evolution equations.
In several instances, treating second-order abstract differential equations directly without always converting them to first-order systems is preferable. The theory of strongly continuous cosine families is a valuable tool for studying second-order problems. We shall use some of the fundamental concepts of cosine family theory []. In [,], the authors provided adequate criteria for controllability of second-order systems in Banach spaces for deterministic and stochastic systems utilizing alternative fixed point theorems and strongly continuous cosine family with nonlinearity meeting Lipschitz condition.
As natural generalizations of deterministic differential equations, random differential equations emerge in a wide range of applications and have been studied by numerous mathematicians, the reader is referred to the papers [,,] for more details. The nature of a dynamic system is determined by the precision of the knowledge we have about the system’s characteristics. A deterministic dynamical system emerges when information about a dynamic system is exact. However, plenty of the relevant data for the identification and assessment of dynamic system characteristics is erroneous, unclear, or ambiguous. In other terms, determining the parameters of a dynamical system is fraught with uncertainty. When we have statistical understanding about the characteristics of a dynamic system, that is, when the knowledge is probable, the standard technique in mathematical modeling of such systems is to employ random or stochastic differential equations.
Controllability is an essential topic in control theory and engineering because it is closely related to pole assignment, quadratic optimal control, observer design and structural decomposition, among other things. Several authors, including Benchohra et al. [,,,], Balachandran et al. [], Mophou et al. [], Wang et al. [], have written extensively in recent years about the problem of controllability for various types of differential equations, neutral functional differential equations, integrodifferential equations differential inclusions and impulsive differential inclusions in Banach spaces.
In [], Balachandran and Sakthivel considered the following integrodifferential system:
where the state takes values in a Banach space X with the norm and the control function is given in , a Banach space of admissible control functions, with U as a Banach space. Here, A is the infinitesimal generator of a strongly continuous semigroup in the Banach space X and g: : are given functions and B is a bounded linear operator from U into X. Here : . The authors employed a fixed-point theorem due to Schaefer.
In [], Yan investigated the controllability of the following fractional-order partial neutral functional integrodifferential inclusions with infinite delay in Banach spaces:
where the unknown takes values in Banach space X with norm is the Caputo fractional derivative of order is the infinitesimal generator of a compact analytic semigroup of uniformly bounded linear operators in X. The authors established sufficient conditions for the controllability for the problem in Banach spaces by relying on analytic semigroups and fractional powers of closed operators and nonlinear alternative of Leray-Schauder type for multivalued maps due to D. O’Regan.
As a continuation of the studies in the preceding publications and in order to expand the controllability results to more problems, in this paper, we consider the following functional differential equation with delay and random effect:
where is a complete probability space, , are given functions, is the infinitesimal generator of of a strongly continuous cosine family of bounded linear operators on , is the phase space, and is a real Banach space. The control function is given in a Banach space of admissible control functions with as a Banach space, and is a bounded linear operator from into
We denote by the element of given by Here represents the history of the state from time up to the present time , we assume that the histories belong to some abstract phases .
Next, we consider the following random problem
where , are given random functions, is as in problem (1), is the phase space, and is a real Banach space. We based our arguments for the main results on Schauder’s fixed theorem [] and random fixed point theorem combined with the family of cosine operators.
Cosine function theory is connected to abstract linear second order differential equations in much the same way as semigroup theory of bounded linear operators is connected to first order partial differential equations, and both are interesting due to their simplicity and clarity. We suggest the papers [,] for fundamental principles and applications of this theory. The following is how this paper is structured. Section 2 provides some preliminary results. Section 3 and Section 4 are devoted to our main results in the cases of infinite fixed delay, and state-dependent delay, respectively. The last part includes an instructive example.
2. Preliminaries
In this section, we will go over some of the notations, definitions, and theorems that will be employed all through the paper. Let :, and consider the Banach space of bounded linear operators from into with the norm
Let be the Banach space of continuous functions x: with the norm
We will adopt an axiomatic definition of the phase space presented in [] and adhere to the terminology employed in []. Then, Let be a seminormed linear space of functions mapping into and verifying the following:
- (A1)
- If x: is continuous on and , then for every the requirements that follows are met.
- (a)
- ;
- (b)
- There exists a positive constant such that ;
- (c)
- There exist two functions independent of x with continuous and bounded, and locally bounded where:
- (A2)
- For the function x in , is a valued continuous function on .
- (A3)
- The space is complete.
Set
Remark 1.
We have
- 1.
- (b) is equivalent to for every .
- 2.
- Since is a seminorm, two elements can satisfy without for all
- 3.
- For all where , we have
Consider the space
Let be the seminorm in given by
Definition 1.
A family of bounded linear operators in the Banach space Ξ is strongly continuous cosine family if
- (I is the identity operator);
- is strongly continuous in ϑ on for each fixed ;
- for all ϑ,
Let be a strongly continuous cosine family in . Define the linked sine family by
We define the infinitesimal generator of the cosine family by
where
Definition 2.
A map is said to be random Carathéodory if
- (i)
- is measurable for all and for all
- (ii)
- is continuous for almost each , and for all
- (iii)
- is measurable for all and for most each
Let be a separable Banach space with the Borel -algebra . The map is a random variable in if for each , is a random operator if is measurable for each , expressed as .
Definition 3
([]). Let be a mapping from Ψ into . A mapping is a random operator with stochastic domain if for all closed and for all open and all . G is continuous if every is continuous. A mapping is a random fixed point of G if for all and and is measurable if for all open .
Lemma 1
([]). Let be measurable with closed, convex and solid (i.e.,) for all . We suppose that there exists measurable with for all Let G be a continuous random operator with stochastic domain such that for every . Then G has a stochastic fixed point.
The mapping of into is a stochastic process if for each , the function is measurable. Now let us recall some fundamental facts of the notion of Kuratowski measure of noncompactness.
Definition 4
([]). Let χ be a Banach space and the bounded subsets of Ξ. The Kuratowski measure of noncompactness is the map given by
and verifies the properties:
- (a)
- is compact (Υ is relatively compact);
- (b)
- (c)
- (d)
- (e)
- (f)
Lemma 2
([]). If is bounded and equicontinuous, then is continuous on Θ and
where , and μ is the Kuratowski measure of noncompactnes on the space Ξ.
3. Controllability Results for the Constant Delay Case
Definition 5.
Definition 6.
A stochastic process is a random mild solution of problem (1) if and the restriction of to the interval Θ is continuous and verifies:
Let
We will need to introduce the following hypotheses:
- is compact for
- The function is random Carathéodory,
- There exist functions and such that for each , is continuous nondecreasing and integrable with:
- There exists a random function where:where
- The linear operator given by:has a pseudo-inverse operator in and there exists a positive constant such that
- For each is continuous and for each is measurable, and for each is measurable.
Theorem 1.
If – are satisfied, then the problem (1) is controllable on
Proof.
Define the control:
We define the operator by: if and for
Using , we will demonstrate that has a fixed point which is a mild solution of (1). This implies that the problem (1) is controllable on Further, we prove that is a random operator. For that, we demonstrate that for any : is a random variable. Then we demonstrate that : is measurable. As the mapping , is measurable by assumption and Let be given by:
is bounded, closed, convex and solid for all Then D is measurable by Lemma 17 in []. Let be fixed, then for any and by , we obtain:
and by and we have
Set
Then, we have
Thus
Thus, we deduce that is a random operator with stochastic domain D and for each □
Claim 1: is continuous.
Let be a sequence where in Y. Then
As is continuous, we obtain
Thus is continuous.
Claim 2: We demonstrate that for every
We apply Schauder’s theorem.
- (a)
- maps bounded sets into equicontinuous sets inLet with , be a bounded set as in Claim 2, and Then
The right-hand of the above inequality tends to zero as since are compact for and strongly continuous, then we obtain the continuity in the uniform operator topology (see [,]).
- (b)
- Let be fixed and let . From assumptions and since is compact, the set
is precompact in , and the set
is precompact in Thus, is continuous and compact. Schauder’s theorem implies that has a fixed point in . Since and a measurable selector of exists, then by Lemma 1, we conclude that has a stochastic fixed point which is a random mild solution of (1).
4. Controllability Results for the State-Dependent Delay Case
In this section we give our main controllability result for problem (2).
Definition 7.
A stochastic process is said to be a random mild solution of problem (2) if and the restriction of to the interval Θ is continuous and verifies equation:
Set
Suppose that is continuous. And,
- The function is continuous from into and there exists a continuous and bounded function where
Remark 2
([]). The hypothesis is satisfied by continuous and bounded functions.
Lemma 3
([]). If is a function such that then
where .
We consider now the hypotheses:
- is compact for in
- The function is random Carathéodory.
- There exist a function and such that for each , is a continuous nondecreasing function and integrable with:
- There exists a function with for each such that for any bounded .
- There exists a random function where:
- The linear operator defined by:has a pseudo-inverse operator which takes values in and there exists a positive constant such that
- For each is continuous and for each is measurable and for each is measurable.
Theorem 2.
Assume that and hold. If
then the random problem (2) is controllable on
Proof.
Using , we define the control:
We define the operator by: if and for by:
Proving that has a fixed point and that (2) is controllable. Further, we demonstrate that is a random operator by showing that for any , : is a random variable. Also, we show that : is measurable, as a mapping , is measurable by and Let be given by:
is bounded, closed, convex and solid for all Then D is measurable. Let be fixed. If , then
and for each , from and , for each we have
Thus, is a random operator with stochastic domain D and for each □
Claim 1: is continuous.
Let be a sequence such that in . Then
As is continuous, then Thus is continuous.
Claim 2: We demonstrate that for every by employing Mönch fixed point theorem [,].
- (a)
- maps bounded sets into equicontinuous sets in .Let with , be a bounded set, and . Then
Thus
Hence
The right-hand of the above inequality tends to zero as , since and are a strongly continuous operator and the compactness of and for thus the continuity in the uniform operator topology.
Further, let be fixed.
- (b)
- Let be a subset of where is bounded and equicontinuous, thus the function is continuous on . By Lemma 2 and the properties of the measure we have for each
Thus
Then
Consequently, , thus for each , and then is relatively compact in . As a result of the Ascoli-Arzelà theorem, is relatively compact in . By Mönch fixed point theorem, we deduce that has a fixed point . As and a measurable selector of exists, by Lemma 1, has a stochastic fixed point which is a mild solution of (2).
5. An Example
Consider the problem:
where is a given function. Let and given by with domain are absolutely continuous,
The operator is the infinitesimal generator of a strongly continuous cosine function on . Furthermore, has discrete spectrum, the eigenvalues are with corresponding normalized eigenvectors
and
- (a)
- is an orthonormal basis of
- (b)
- If , then
- (c)
- For ,, and the associated sine family isConsequently, is compact for all and
- (d)
- If we denote the group of translations on bywhere is the extension of x with period thenwhere D is the infinitesimal generator of the group on
6. Conclusions
In this work, we have presented some existence and controllability results for two classes of second order functional differential equations with delay and random effects. Our arguments are based on a random fixed point theorem with a stochastic domain. Next, we prove that our problems are controllable. On the other hand, we have given an illustrative example which indicates the applicability of this study. Some of the results in this direction constitute our future research plan. More work can be done by changing and generalizing the conditions, the functional spaces, or even extend the study to some fractional differential problems.
Author Contributions
All authors contributed to the study conception and design, equally. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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