Research Article | Open Access
Hugo Leiva, Miguel Narvaez, Zoraida Sivoli, "Controllability of Impulsive Semilinear Stochastic Heat Equation with Delay", International Journal of Differential Equations, vol. 2020, Article ID 2515160, 10 pages, 2020. https://doi.org/10.1155/2020/2515160
Controllability of Impulsive Semilinear Stochastic Heat Equation with Delay
LaSalle wrote the following: “it is never possible to start the system exactly in its equilibrium state, and the system is always subject to outside forces not taken into account by the differential equations. The system is disturbed and is displaced slightly from its equilibrium state. What happens? Does it remain near the equilibrium state? This is stability. Does it remain near the equilibrium state and in addition tend to return to the equilibrium? This is asymptotic stability.” Continuing with what LaSalle said, we conjecture that real-life systems are always under the influence of impulses, delays, memory, nonlocal conditions, and noises, which are intrinsic phenomena no taken into account by the mathematical model that is representing by a differential equation. For many control systems in real life, delays, impulses, and noises are natural properties that do not change their behavior. So, we conjecture that, under certain conditions, the abrupt changes, delays, and noises as perturbations of a system do not modify certain properties such as controllability. In this regard, we prove the interior -controllability of the semilinear stochastic heat equation with impulses and delay on the state variable, and this is done by using new techniques avoiding fixed point theorems employed by Bashirov et al.
In this paper, we prove the interior approximate -controllability of the semilinear stochastic heat equation with multiplicative noise, impulses, and delay on the state variable. This is done by using the result from Leiva ; Acosta Leiva ; and new techniques avoiding fixed point theorems employed by Bashirov et al. [3–5]. In this regard, we will prove the interior approximate -controllability of the semilinear stochastic heat equation with multiplicative noise, impulses, and delay:where is a bounded domain in , denotes its boundary, is an open nonempty subset of , denotes the characteristic function of the set , is a control processes -valued, the noise is a colored noise valued on with spatial correlation given byand is a -valued -measurable random variable with respect to filtration , where . The nonlinear terms are smooth enough such that system (1) admits unique mild solutions for each control and satisfies the following property:
The term white-noise is denoted by , where is a Gaussian process with zero mean and covariance given by (2). The noise behaves as a Brownian motion with respect to the time variable, and it has a correlated spatial covariance.
There are many practical examples of impulsive control systems which are modeled by impulsive differential equations (for more information, see the monographs: Samoilenko and Perestyuk ; Franco and Nieto ; Sun and Zhang ; Lakshmikanthan, Bainov and Simeonov ; He and Yu ; Luo and Shen ). The controllability of impulsive evolution equations has been studied recently for several authors, but most them study the exact controllability only (to mention, Radhakrishnan and Balachandran ; Chalishajar ; Selvi and Mallika ). To our knowledge, there are a few works on approximate controllability of impulsive semilinear evolution equations (to mention, Chen and Li  and Sakthivel and Anandhi ). Recently, in the study of Carrasco, Leiva, Sanchez, and Tineo ; Leiva ; Leiva and Merentes , the approximate controllability of semilinear evolution equations with impulses has been studied applying Rothe’s fixed point theorem. Contrained controllability of finite-dimensional semilinear systems with delayed controls has been studied by Klamka [19, 20] where the author gives sufficient conditions for contrained local relative controllability applying a generalized open mapping theorem. Also, Klamka  gave necessary and sufficient conditions for different kinds of stochastic relative controllability in a given time interval which are proved for stochastic finite-dimensional linear systems with multiple delays in control.
The existence of solutions for impulsive evolution equations with delays has been studied by Hernandez, Sakthivel, and Tamaka ; Abada, Benchohra, and Hammouche ; Shikharchan and Baburao  and Chang [25, 26]. Besides, impulsive and stochastic effects appear in real-life systems. Moreover, a lot of dynamical systems have structure variables subject to stochastic abrupt changes, which may result from sudden phenomena such as stochastic failures and repair of components, quick environmental changes, and changes in the interconnections of subsystems (see Mao ). In the stochastic context, we can mention some papers related to impulsive and delay stochastic systems: Lijuan, Junping, and Jitao ; Sakthivel ; Sukavanam and Kumar ; Parthasarathy and Sathya .
The exact and approximate controllability is known for determinist systems; but the exact controllability was introduced as a concept for linear finite-dimensional systems by Kalman in the 50s. Nevertheless, the extension of this concept to infinite dimensional systems is too strong. Therefore, the approximate controllability was introduced as a weakened version of the exact controllability. However, the exact and approximate controllability cannot be a property of stochastic systems, and this needs to be a weaker concept than the approximate controllability concepts in order to extend them to the stochastic systems. Then, the concept of the -controllability is introduced. A control system is -controllable, if given an arbitrary , it is possible to steer from the point to within a distance from all points in the state space at time with probability close to one. The approximate controllability and -controllability concepts are equivalent for the linear system but are different for nonlinear stochastic systems. This concept and generalization are defined in Bashirov et al. [5, 31]. In this context, we used the -controllability which is a weaker version of -controllability.
The main objective of this article is to prove the interior -controllability of the semilinear stochastic heat equation with impulses, delay, and multiplicative noises (1) simultaneously, under appropriate conditions presented above. For this, we apply the new technique presented in Bashirov et al. [3, 4, 31, 32]. In the literature, -controllability for such systems, only a few works such as Bashirov and an article by Sukavanam and Kumar , has been reported.
In this section, we introduce notations, definitions, and preliminaries which are used to write (1) as an abstract differential equation.
Let , , and be separable Hilbert spaces and be a complete probability space with a probability measure on . Let be a Wiener processes with values in and covariance nonnegative operator ( is the space of bounded linear operators on ). If the control system is stochastic, we denote by the smallest -field generated by . We assume that there exists a complete orthonormal set in and a bounded sequence of nonnegative real numbers such that with . Let be a sequence of real-valued one-dimensional standard Brownian motions mutually independent over such that .
Denoted by , the space of all -Hilbert-Schmidt operators from to with norm defined by
denotes the expectation of a random variable and denotes the conditional expectation of . Let denote the Hilbert space of all -measurable square-integrable random variables with values in . Moreover, let denote the Hilbert space of all square-integrable and -measurable processes with values in with topology given by the norm:
The control , where is the family -valued measurable and -adapted processes with norm topology given by
We consider the function defined by with being the delay. Therefore, the initial condition can be written as .
We shall denote by the set consisting of all -measurable bounded random processes with value in :satisfying
When the control system is stochastic and completely observable, then is a natural filtration of . In this case, (see Bashirov et al. ). So, we shall consider the following notation:where
Definition 1. A stochastic control system is said to be -controllable if
3. Abstract Formulation of the Problem
This section is devoted to set system (1) as an abstract control system in a suitable Hilbert space. To this end, we recall that the operator with Dirichlet boundary condition in has the following spectral decomposition , where denotes the eigenvalues of , each one with finite multiplicity equal to the dimension of the corresponding eigenspace. Therefore, the following properties for hold:(i)For all , we have where is the inner product in , is a complete orthonormal set of eigenvectors of , and So, is a family of complete orthogonal projections in and .(ii) generates an analytic semigroup given by Therefore, system (1) can be written as abstract functional differential equations with impulses and noses (see Acosta-Leiva . where , , , is a bounded linear operator, and is defined by , , and the operators , , are defined by
Proposition 1. Under condition (3) the function and satisfies
4. Approximate Controllability of the Linear Heat Equation
Since the associated linear stochastic heat equation is approximately controllable in any interval of the form , with , we shall recall some properties and characterizations of the approximate controllability of linear deterministic evolution equations and linear stochastic evolution equations. In this regard, we consider the corresponding linear stochastic heat equation:
Note that, for all random variable -measurable and , the initial value problemadmits only one mild solution given by
We also consider the deterministic system corresponding to (20), and for all and , the initial value problemadmits only one mild solution given by
Definition 3. The stochastic linear system (20) is said to be approximately controllable on if for every initial state and final state and any there exists a control , , such that the mild solution of (20) corresponding to verifieswhereIt is known that approximately controllability of the stochastic linear system (20) and deterministic linear system (22) for linear infinite dimensional systems are equivalent (see Mahmudov ). Now, we define the following operator.
Definition 4. (see ). For system (22), we define the following concept: the controllability maps , defined bysatisfy the following relation:The adjoint of these operators , are given byThe controllability operators are given by is defined byThe following lemma holds in general for a linear-bounded operator between Hilbert spaces and (see Bashirov et al. ; Curtain and Pritchard ; Curtain and Zwart  and Leiva et al. ).
Lemma 1. The following statements are equivalent to the approximate controllability of the linear system (20) on .
(a)(b)(c), in (d)
Remark 1. Lemma 1 implies that, for all , we havewhere
So, and the error of this approximation is given by the formula:and the family of linear operators , defined for byis an approximate inverse for the right of the operator , in the sense thatin the strong topology.
Lemma 2. if and only if linear system (22) is approximately controllable on . Moreover, given an initial state and a final state , we can find a sequence of controls , wheresuch that the solutions of the initial value problemsatisfiesi.e.,
5. -Controllability of the Semilinear Stochastic System
In this section, we shall prove the main result of this paper, the interior -controllability of the heat equation with impulses, delay, and multiplicative noise (1), which is equivalent to prove the -controllability of system (16). To this end, for all and , the initial value problemadmits only one mild solution given bywith .
Proposition 2 (see ). If , thenNow, we are ready to present and prove the main result of this paper, the -controllability of the semilinear heat equation with impulses, delay, and multiplicative noise.
Proof. Given , a final state , and , we want to find a sequence of control steering the system from to an -neighborhood of on time in probability. Precisely, for , there exists control such that the corresponding solution of (39) satisfiesConsider any process control and the corresponding solution of the initial value problem (39). For , we define the control aswhere since is -measurable and .
Now, since , the corresponding solution of the initial value problem (39) at time can be written as follows:Therefore,Hence,Thus,Also, the corresponding mild solution of the initial value problem of linear solution (22) at time is given byor equivalentlySince is -measurable, and also is -measurable, it is measurable with respect to the smaller field . On the other hand, we have thatand subtracting (49) from (48), we getTaking conditional expectation with respect to and using the fact that the termis independent of , we haveTherefore, putting and applying Jensen’ inequality, we have thatIf we take and , then and . So, we obtain the following estimate:where .
Hence,or equivalently, by orthogonal projection property of conditional expectation, we have thatFrom equation (51), Lemma 1(d), and Proposition 2, we get thatThen, is dominated by an integrable random variable. Consequently, for every ,Therefore, for fixed , we can choose such thatThere exists such thatThen, there exists a sequence of controls such thatSince mean square convergence implies convergence in probability, we obtainThis completes the proof of the theorem.
In this article the approximate -controllability was proved for the stochastic semilinear heat equation with impulse, delay, and multiplicative noise. For this, we avoid the method of fixed point theorems by applying a new alternative method due to Bashirov et al. This technique can be used to prove the -controllability of the stochastic Benjamin Bona Mohany equation with impulses and delays, for the stochastic strongly damped wave equation under influence of impulses and delays and stochastic partial differential equations modelling the structural damped vibrations of a string or beam under the influence of impulses and delays.
Considering Theorem 1, there are many systems that do not satisfy the sufficient condition (3) and still controllable. In fact, if we change condition (3) by the following condition:wherethe system is still -controllable by using ideas from Leiva et al. [1, 2, 37].
The data used in the research to support the findings of this study are purely Bibliographic and from scientific publications, which are included in the article with their respective citations.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
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