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The document discusses approximate controllability results for impulsive linear fuzzy stochastic differential equations under nonlocal conditions. It presents sufficient conditions for the approximate controllability of such systems using Banach fixed point theorems, stochastic analysis, and fuzzy processes. The main result establishes approximate controllability of impulsive linear fuzzy stochastic differential equations by verifying assumptions on the system using fixed point theorems.
We disclose a simple and straightforward method of solving ordinary or linear partial differential equations of any order and apply it to solve the generalized Euler-Tricomi equation. The method is easier than classical methods and also didactic.
Date: Jan, 10, 202
Existence and Controllability Result for the Nonlinear First Order Fuzzy Neut...ijfls
In this paper, we devoted study the existence and controllability for the nonlinear fuzzy neutral integrodifferential equations with control system in E_N. Moreover we study the fuzzy solution for the normal, convex, upper semicontinuous and compactly supported interval fuzzy number. The results are obtained by using the contraction principle theorem. An example to illustrate the theory.
How to Solve a Partial Differential Equation on a surfacetr1987
Familiar techniques of separation of variables and Fourier series can be used to solve a variety of pde based on domains in the plane, however these techniques do not extend naturally to surface problems. Instead we look to take a computational approach. The talk will cover the basics of finite difference and finite element approximations of the one dimensional heat equation and show how to extend these ideas on to surfaces. If time allows, we will show numerical results of an optimal partition problem based on a sphere. No background knowledge of pde or computation is required.
On Frechet Derivatives with Application to the Inverse Function Theorem of Or...BRNSS Publication Hub
In this paper, the Frechet differentiation of functions on Banach space was reviewed. We also investigated that it is algebraic properties and its relation by applying the concept to the inverse function theorem of the ordinary differential equations. To achieve the feat, some important results were considered which finally concluded that the Frechet derivative can extensively be useful in the study of ordinary differential equations.
We disclose a simple and straightforward method of solving ordinary or linear partial differential equations of any order and apply it to solve the generalized Euler-Tricomi equation. The method is easier than classical methods and also didactic.
Date: Jan, 10, 202
Existence and Controllability Result for the Nonlinear First Order Fuzzy Neut...ijfls
In this paper, we devoted study the existence and controllability for the nonlinear fuzzy neutral integrodifferential equations with control system in E_N. Moreover we study the fuzzy solution for the normal, convex, upper semicontinuous and compactly supported interval fuzzy number. The results are obtained by using the contraction principle theorem. An example to illustrate the theory.
How to Solve a Partial Differential Equation on a surfacetr1987
Familiar techniques of separation of variables and Fourier series can be used to solve a variety of pde based on domains in the plane, however these techniques do not extend naturally to surface problems. Instead we look to take a computational approach. The talk will cover the basics of finite difference and finite element approximations of the one dimensional heat equation and show how to extend these ideas on to surfaces. If time allows, we will show numerical results of an optimal partition problem based on a sphere. No background knowledge of pde or computation is required.
On Frechet Derivatives with Application to the Inverse Function Theorem of Or...BRNSS Publication Hub
In this paper, the Frechet differentiation of functions on Banach space was reviewed. We also investigated that it is algebraic properties and its relation by applying the concept to the inverse function theorem of the ordinary differential equations. To achieve the feat, some important results were considered which finally concluded that the Frechet derivative can extensively be useful in the study of ordinary differential equations.
International Journal of Mathematics and Statistics Invention (IJMSI) inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Stability analysis of steady state solutions of Huxley equation using Fourier mode stability analysis in two cases is investigated. Firstly when the amplitude is constant and secondly when the amplitude is variable and the results were found to be: The solutions u1 = 0 and u1 = 1 are always stable while the solutions u1 = a and u1 = u1(X) are conditionally stable. In the second case, a comparison between the analytical solution and the numerical solution of Galerkin method is done and the results are the same.
Numerical Solution of Nth - Order Fuzzy Initial Value Problems by Fourth Orde...IOSR Journals
In this paper, a numerical method for Nth - order fuzzy initial value problems (FIVP) based on
Seikkala derivative of fuzzy process is studied. The fourth order Runge-Kutta method based on Centroidal Mean
(RKCeM4) is used to find the numerical solution and the convergence and stability of the method is proved. This
method is illustrated by solving second and third order FIVPs. The results show that the proposed method suits
well to find the numerical solution of Nth – order FIVPs.
Solvability of system of intuitionistic fuzzy linear equationsijfls
In this paper, it is shown that for a system of intuitionistic fuzzy linear equations of the form AÄx = b is
said to be solvable if, for a definite solution x(A;b) , AÄ x(A;b) = b holds, otherwise unsolvable. In
general AÄ x(A;b) £ b holds always, so taking a tolerable solution of an unsolvable system, keeping
right hand side of the system constant, modification of the left hand side intuitionistic fuzzy matrix A has
been made, such that, the system will be solvable with the help of Chebychev Approximation. The maximum
solution of the system is also defined here.
Periodic Function, Dirichlet's Condition, Fourier series, Even & Odd functions, Euler's Formula for Fourier Coefficients, Change of Interval, Fourier series in the intervals (0,2l), (-l,l) , (-pi, pi), (0, 2pi), Half Range Cosine & Sine series Root mean square, Complex Form of Fourier series, Parseval's Identity
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
We disclose a simple and straightforward method of solving single-order linear partial differential equations. The advantage of the method is that it is applicable to any orders and the big disadvantage is that it is restricted to a single order at a time. As it is very easy compared to classical methods, it has didactic value.
Divulgamos um simples e direto método de resolução de equações diferenciais parciais lineares de ordem única. A vantagem do método é ser aplicável a ordens quaisquer e, a grande desvantagem, é ser restrito a uma única ordem, de cada vez. Por ser muito fácil em comparação com os métodos clássicos, possui grande valor didático.
The paper reports on an iteration algorithm to compute asymptotic solutions at any order for a wide class of nonlinear
singularly perturbed difference equations.
Output Regulation of SPROTT-F Chaotic System by State Feedback ControlAlessioAmedeo
This paper solves the output regulation problem of Sprott-F chaotic system, which is one of the classical chaotic systems discovered by J.C. Sprott (1994). Explicitly, for the constant tracking problem, new state feedback control laws have been derived for regulating the output of the Sprott-F chaotic system. Our controller design has been carried out using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott-F chaotic system has important applications in many areas of Science and Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-F chaotic system.
Existence of Solutions of Fractional Neutral Integrodifferential Equations wi...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Mathematics and Statistics Invention (IJMSI) inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Stability analysis of steady state solutions of Huxley equation using Fourier mode stability analysis in two cases is investigated. Firstly when the amplitude is constant and secondly when the amplitude is variable and the results were found to be: The solutions u1 = 0 and u1 = 1 are always stable while the solutions u1 = a and u1 = u1(X) are conditionally stable. In the second case, a comparison between the analytical solution and the numerical solution of Galerkin method is done and the results are the same.
Numerical Solution of Nth - Order Fuzzy Initial Value Problems by Fourth Orde...IOSR Journals
In this paper, a numerical method for Nth - order fuzzy initial value problems (FIVP) based on
Seikkala derivative of fuzzy process is studied. The fourth order Runge-Kutta method based on Centroidal Mean
(RKCeM4) is used to find the numerical solution and the convergence and stability of the method is proved. This
method is illustrated by solving second and third order FIVPs. The results show that the proposed method suits
well to find the numerical solution of Nth – order FIVPs.
Solvability of system of intuitionistic fuzzy linear equationsijfls
In this paper, it is shown that for a system of intuitionistic fuzzy linear equations of the form AÄx = b is
said to be solvable if, for a definite solution x(A;b) , AÄ x(A;b) = b holds, otherwise unsolvable. In
general AÄ x(A;b) £ b holds always, so taking a tolerable solution of an unsolvable system, keeping
right hand side of the system constant, modification of the left hand side intuitionistic fuzzy matrix A has
been made, such that, the system will be solvable with the help of Chebychev Approximation. The maximum
solution of the system is also defined here.
Periodic Function, Dirichlet's Condition, Fourier series, Even & Odd functions, Euler's Formula for Fourier Coefficients, Change of Interval, Fourier series in the intervals (0,2l), (-l,l) , (-pi, pi), (0, 2pi), Half Range Cosine & Sine series Root mean square, Complex Form of Fourier series, Parseval's Identity
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
We disclose a simple and straightforward method of solving single-order linear partial differential equations. The advantage of the method is that it is applicable to any orders and the big disadvantage is that it is restricted to a single order at a time. As it is very easy compared to classical methods, it has didactic value.
Divulgamos um simples e direto método de resolução de equações diferenciais parciais lineares de ordem única. A vantagem do método é ser aplicável a ordens quaisquer e, a grande desvantagem, é ser restrito a uma única ordem, de cada vez. Por ser muito fácil em comparação com os métodos clássicos, possui grande valor didático.
The paper reports on an iteration algorithm to compute asymptotic solutions at any order for a wide class of nonlinear
singularly perturbed difference equations.
Output Regulation of SPROTT-F Chaotic System by State Feedback ControlAlessioAmedeo
This paper solves the output regulation problem of Sprott-F chaotic system, which is one of the classical chaotic systems discovered by J.C. Sprott (1994). Explicitly, for the constant tracking problem, new state feedback control laws have been derived for regulating the output of the Sprott-F chaotic system. Our controller design has been carried out using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott-F chaotic system has important applications in many areas of Science and Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-F chaotic system.
Existence of Solutions of Fractional Neutral Integrodifferential Equations wi...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Existance Theory for First Order Nonlinear Random Dfferential Equartioninventionjournals
In this paper, the existence of a solution of nonlinear random differential equation of first order is proved under Caratheodory condition by using suitable fixed point theorem. 2000 Mathematics Subject Classification: 34F05, 47H10, 47H4
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
HYBRID SLIDING SYNCHRONIZER DESIGN OF IDENTICAL HYPERCHAOTIC XU SYSTEMS ijitjournal
In this paper, new results have been obtained via sliding mode control for the hybrid chaos synchronization
of identical hyperchaotic Xu systems (Xu, Cai and Zheng, 2009). In hybrid synchronization of master and
slave systems, the odd states are completely synchronized, while the even states are anti-synchronized. The
stability results derived in this paper for the hybrid synchronization of identical hyperchaotic Xu systems
are established using Lyapunov stability theory. MATLAB simulations have been shown for the numerical
results to illustrate the hybrid synchronization schemes derived for the identical hyperchaotic Xu systems.
Stability analysis for nonlinear impulsive optimal control problemsAI Publications
We consider the generic stability of optimal control problems governed by nonlinear impulsive evolution equations. Under perturbations of the right-hand side functions of the controlled system, the results of stability for the impulsive optimal control problems are proved given set-valued theory.
We present a class of continuous, bounded, finite-time stabilizing controllers for the tranlational and double integrator based on Bhat and Bernstein's work of IEEE Transactions on Automatic Control, Vol. 43, No. 5, May 1998
Stochastic Processes describe the system derived by noise.
Level of graduate students in mathematics and engineering.
Probability Theory is a prerequisite.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
On the Principle of Optimality for Linear Stochastic Dynamic System ijfcstjournal
In this work, processes represented by linear stochastic dynamic system are investigated and by
considering optimal control problem, principle of optimality is proven. Also, for existence of optimal
control and corresponding optimal trajectory, proofs of theorems of necessity and sufficiency condition are
attained.
Errors in the Discretized Solution of a Differential Equationijtsrd
We study the error in the derivatives of an unknown function. We construct the discretized problem. The local truncation and global errors are discussed. The solution of discretized problem is constructed. The analytical and discretized solutions are compared. The two solution graphs are described by using MATLAB software. Wai Mar Lwin | Khaing Khaing Wai "Errors in the Discretized Solution of a Differential Equation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27937.pdfPaper URL: https://www.ijtsrd.com/mathemetics/applied-mathamatics/27937/errors-in-the-discretized-solution-of-a-differential-equation/wai-mar-lwin
STATE FEEDBACK CONTROLLER DESIGN FOR THE OUTPUT REGULATION OF SPROTT-H SYSTEMijistjournal
This paper investigates the problem of state feedback controller design for the output regulation of SprottK chaotic system, which is one of the simple, classical, three-dimensional chaotic systems discovered by J.C. Sprott (1994). Explicitly, we have derived new state feedback control laws for the constant tracking problem for the Sprott-H system. The state feedback control laws have been derived using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott H chaotic system has important applications in Electronics and Communication Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-H chaotic system.
STATE FEEDBACK CONTROLLER DESIGN FOR THE OUTPUT REGULATION OF SPROTT-H SYSTEMijistjournal
This paper investigates the problem of state feedback controller design for the output regulation of SprottK chaotic system, which is one of the simple, classical, three-dimensional chaotic systems discovered by J.C. Sprott (1994). Explicitly, we have derived new state feedback control laws for the constant tracking problem for the Sprott-H system. The state feedback control laws have been derived using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott H chaotic system has important applications in Electronics and Communication Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-H chaotic system.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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International Journal of Fuzzy Logic Systems (IJFLS)Wireilla
International Journal of Fuzzy Logic Systems (IJFLS)
https://wireilla.com/ijfls/current.html
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON THE FUZZY LOGIC
Hamed Khosravi and Seyed Ghorshi
School of Science and Engineering, Sharif University of Technology,
International Campus, Kish Island, Iran.
ABSTRACT
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model.
KEYWORDS
Mobile robot, Fuzzy logic, Effective redirecting
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...Wireilla
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is
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center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile
robot are determined by the desired fuzzy structures which are applied to its kinematic model.
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APPROXIMATE CONTROLLABILITY RESULTS FOR IMPULSIVE LINEAR FUZZY STOCHASTIC DIFFERENTIAL EQUATIONS UNDER NONLOCAL CONDITIONS
1. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
DOI : 10.5121/ijfls.2015.5403 27
APPROXIMATE CONTROLLABILITY RESULTS
FOR IMPULSIVE LINEAR FUZZY STOCHASTIC
DIFFERENTIAL EQUATIONS UNDER
NONLOCAL CONDITIONS
S.Narayanamoorthy1
and S.Sowmiya2
1
Department of Mathematics,
2
Department of Applied Mathematics
Bharathiar University, Coimbatore-641 046, INDIA.
ABSTRACT
In this paper, the approximate controllability of impulsive linear fuzzy stochastic differential
equations with nonlocal conditions in Banach space is studied. By using the Banach fixed point
theorems, stochastic analysis, fuzzy process and fuzzy solution, some sufficient conditions are given for
the approximate controllability of the system.
KEY WORDS
Approximate controllability, impulsive linear fuzzy stochastic differential equations, fuzzy solution,
fixed point theorems, nonlocal conditions.
2010 MSC: 03E72, 39A50, 93B05, 49N25, 47H10
1. INTRODUCTION
Differential equations have been used in modeling the dynamics of changing processes. A great
dense of the modeling, development has been accompanied by a rich theory of differential
equations. Freshly, stochastic differential equations (SDEs) occur in the mathematical modeling
of various fields in physics and engineering science. Among them, several properties of SDEs
such as existence, controllability, and stability are studied for the linear and nonlinear equations.
But in many situations, it is useful to investigate the linear stochastic differential equations
directly discussed by Daniel [2]. The properties and applications are presented in [5].
Fuzzy set theory introduced by Zadeh [19] is a generalization of abstract set theory. Semwal et. al
[14] studied the less computationally intensive fuzzy logic based controller for humanoid push
recovery. The theory of Impulsive differential equations have been developed in modeling
impulsive problems in physics, population dynamics, ecology, biological systems, robotics,
optimal control and so forth. In [6, 7, 9] these types of impulsive effects and differential systems
were studied. The nonlocal condition, which is a generalization of the classical initial condition,
was motivated by physical problems. Among others, we refer to the papers in [1,4,13]. In general,
fixed point theorems are very useful classes of result that give us the conditions under which for
some function f. The Sadovskii fixed point theorem and the theory of strongly continuous cosine
families of operators are used to study the sufficient conditions for the controllability of the
system considered and that are discussed in [3, 14,17].
2. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
28
The concept of the controllability has played a central role during the history of modern control
theory. The approximate controllable systems are more common and very often approximate
controllability is completely sufficient in applications. Therefore, it is important and necessary to
study the weaker concept of controllability, namely approximate controllability for linear and
nonlinear differential systems. In [10,11] these types of controllability properties and conditions
were discussed.
In the literature there are only some papers that deal with the approximate controllability of fuzzy
differential and linear fuzzy differential systems, likewise approximate controllability of second
order stochastic systems as discussed in [17]. Subalakshmi and Balachandran [16] studied the
nonlinear stochastic impulsive integrodifferential system’s approximate controllability.
Mahmudov and Zorlu [8] discussed the concept of the approximate controllability of semilinear
neural systems in Hilbert space. Narayanamoorthy and Sowmiya [12] presented the concept of
the approximate controllability result for nonlinear impulsive neural fuzzy stochastic differential
equation with nonlocal conditions. It should be mentioned that there is no work done on the
approximate controllability of linear fuzzy stochastic differential equations. Motivated by the
above consideration in this paper, we examine the approximate controllability for impulsive
linear fuzzy stochastic differential equation with nonlocal conditions.
The rest of the paper is organized as follows. In the following section, we give the necessary
preliminaries, definitions, lemmas and theorems. In section 3, we deduce the main result on the
approximate controllability result for linear fuzzy stochastic differential systems. Finally, in
Section 4 includes the conclusion.
2. PROBLEM FORMULATION AND PRELIMINARIES
Here, first we define some properties, theorems and lemma’s and also recalls some basic
definitions which are all used in this paper. A fuzzy set of Rn is a function u: Rn → [0, 1].
For each fuzzy set u, we denote by [u]α = x ∈ Rn: u(x) ≥ α for any α ∈ [0, 1], its α − level
set.
Let u, v be fuzzy sets of Rn. It is well known that [u]α = [v]α for each α ∈ [0, 1] implies u
=v. Let En denote the collection of all fuzzy sets of Rn that satisfies the following
conditions:
• u is normal
• fuzzy convex
• upper semicontinuous and
• [u]0 is compact.
We call u ∈ En is an n-dimensional fuzzy number.
Definition 2.1. If u ∈ En , and [u]α is a hyperrectangle, that is, [u]α can be
represented by , that is for every
α ∈[0, 1], where ∈R with when α ∈(0, 1],i=1,2,...,n, then we call u is a fuzzy
n-cell number. We denote the collection of all fuzzy n-cell numbers by L(En
).
3. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
29
Theorem 2.2.
For any u∈L(En
) with [u]α
= (α ∈[0, 1]), there exist a unique (u1,u2,...,un)∈(En
)
such that [u]α
= (i=1,2,...,n and α ∈[0, 1]).
Conversely, for any (u1,u2,...,un)∈(En
) with [u]α
= (i=1,2,...,n and α ∈[0, 1]), there exit a
unique u∈L(En
) such that [u]α
= (α ∈[0, 1]).
Definition 2.3. The complete metric DL on )n
is defined by
10 1 0 1
( , ) sup ([ ] ,[ ] ) sup max{| |,| |}L L il il ir ir
i n
D u v d u v u v u vα α α α α α
α α ≤ ≤< ≤ < ≤
= = − −
(2.1)
for any u,v∈ L )n
, which satisfied ( , ) ( )L Ld u w v w d u v+ + = + .
Definition 2.4. Let , ([0, ]) : ( ) )i n
Nu v C T E∈ , then
1
0
( , ) sup ( ( ), ( )).L
t T
H u v D u t v t
≤ ≤
=
(2.2)
Definition: 2.5 [17]. A stochastic process x is said to be a mild solution of (3.1) if the following
conditions are satisfied:
a. x(t, )ω is a measurable function from J ×Ω to H and x(t) is Ft -adapted,
b.
2
E x(t) < ∞ for each t J∈ ,
c. ( ) ( ) ( ) ( ( )). , 1 .i i i i ix x x I x x X i mτ τ τ τ+ −
∆ = − = ∈ ≤ ≤
d. For each 2u L (J,U)F
∈ , the process x satisfies the following integral equation
1
0
0 0
0
( ) ( ,0)[ ( )] ( , ) ( )
( , ) ( , ( )) ( , ) ( , ( )) ( )
( , ) ( ( )), .
i
t
t t
i i i
t t
x t U t x x U t s Bu s ds
U t s f s x s ds U t s g s x s dW s
U t t I x t t J
µ
−
≤ ≤
= − +
+ +
+ ∈
∫
∫ ∫
∑
(2.3)
Definition: 2.6. Let , ( : )n
x y C I E∈ , here I be a real interval. A mapping : Nx I E→ is called a fuzzy
process. We denote,
[ ( )] [ ( ), ( )], , 0 1.l rx t x t x t t Iα α α
α= ∈ < ≤
The derivative ( )x t′ of a fuzzy process x is defined by
[ ( )] [( ) ( ),( ) ( )], , 0 1l rx t x t x t t Iα α α
α′ ′ ′= ∈ < ≤
provided that is equation defines a fuzzy ( ) Nx t E′ ∈ .
4. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
30
h
Definition: 2.7. The fuzzy process :[0, ] ( )i n
Nx T E→ with α-level set
1
[ ( )] [ , ]
n
il ir
i
x t x xα α α
=
= ∏ is a fuzzy
solution of (3.1) with homogenous term iff
( )'( ) min{ ( ) : , , }
( )'( ) min{ ( ) : , , }
il il ik
ir ir ik
x t A t x j k l r
x t A t x j k l r
a a a
a a a
= =
= = (2.4)
and
0 0(0) ( ) , (0) ( ) , 1,2,..., .il iril il il ir ir irx g x x x g x x i na a a a a a a a
+ = + = =
Lemma 2.8. Assume that '
hx B∈ , then for t ∈ I, x∈ Bh . Moreover,
0
[0, ]
| ( ) | sup ( )t Bh Bh
s t
l x t x x l x s
∈
≤ ≤ +
where
0
( ) .l h t dt
−∞
= < ∞∫
Note 2.9. Define '' '
0: 0h h hB z B z B= ∈ = ∈ . For any ''
hz B∈ ,
''
0 sup | ( ) |: [0, ]Bh Bh
z z z s s b= + ∈
sup| ( )|: [0, ],z s s b= ∈
and thus ''
( , )hB ⋅ is a Banach space. Set
'
, , :(( ] ) ( ) , 0 .r Bh
B z PC b X z t r t b= ∈ −∞ ≤ ≤ ≤
Clearly Br is a nonempty, bounded, convex and closed set in '
hB . Then for any z ∈ Br ,
from Lemma [2.4], we have
t t t tBh Bh Bh
z y z y+ ≤ +
( )0 0
[ 0 , ] [0 , ]
sup ( ) sup ( ) 2.5Bh Bh
s b s b
z l z s y l y s
∈ ∈
≤ + + +
'
1( (0) ) Bh
l r M rφ φ≤ + + =
for each t ∈ J, z ∈ Br , we have by above equation and (A2 )
1 1 '
sup ( ) ( ) ,t t Bh
t J
z t y t l z y l r− −
∈
+ ≤ + ≤
(2.6)
( ( ) ( ) (sup ( ) ( ) )k k k k
t J
I z t z t d z t y t+ −
∈
+ ≤ +
1 '
( ), 1,2,..., .kd l r k m−
≤ =
5. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
31
0
Let xb (x0 ; u) be the state value of (3.1) at terminal time b corresponding to the control
u and initial value x0 = φ ∈ Bh. Introduce the set R(b, x0 ) = xb (x0 ; u)(0) :
2
u(·) L (J,U)∈ which is called the reachable set at terminal time b, its closure in X is
denoted by 0,( ).R b x
Definition 2.10. If 0( ),R b x X= then the System (3.1) is approximately controllable on
the interval J. It is convenient at this point to define operators
* *
0
0
( , ) ( , )U a s BB U a s ds
α
α
Γ = ∫
1
0 0( , ) ( , )R Iα α
α α −
Γ = Γ
(D): 0( , ) 0 0R asα
α α α +
Γ → → is strong operator topology. It is known that assumption
(D) holds iff the linear system
0( ) ( ) ( ), (0)x t Ax t Bu t x x= + =&
is approximately controllable on J.
The following theorem gives a formula for a control transferring the initial state x0 to
some neighborhood of xa at time a.
Theorem 2.11.
For arbitrary xa ∈ X , the control
* *
0( ) ( ) ( , ) ( ( ))u t B S a t R p xα
α= − Γ ⋅
Where
0
0
( ( )) ( )[ ( )] ( ) ( ) ( )
a
ap x x S a x g x S a s F s x s ds⋅ = − − − −∫ (2.7)
1 10
( ) ( ) ( ) ( ) ( ) ( )( )( ( ))
an m
k k j j j
k j
S a s S a s G s x s dW s S a t I x t−
= =
− − − − −∑ ∑∫
1
0 0
0
( ) ( ) [ ( )[ ( )] ( ) ( ) ( )
a
a
ax a x I S a x g x S a s F s x s dsα α −
= − + Γ − − −∫ (2.8)
1 10
( ) ( ) ( ) ( ) ( ) ( )( )( ( ))]
an m
k k j j j
k j
S a s S a s G s x s dW s S a t I x t−
= =
− − − − −∑ ∑∫ .
6. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
32
N
3. MAIN RESULT
In this section, we verify that the approximate controllability result for impulsive linear
fuzzy stochastic differential equation condition by using Banach fixed point theorem. Let us
consider the impulsive linear fuzzy stochastic differential equation in( )i n
NE .
1
( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )
n
k k
k
dx t Ax t F t x t dt Bu t dt G t x t dW t
=
= + + + ∑
( ) ( ) ( ) ( ( )),j j j j jx t x t x t I x t x X+ −
∆ = − = ∈
(3.1)
0(0) ( ) ( )i n
Nx g x x E+ = ∈
With fuzzy coefficient :[0, ] ( )i n
NA T E→ , 0 ( )i n
Nx E∈ is a initial value, and :[0, ] ( )i n
Nu T E→
is a control function.
To establish the result, we introduce the following assumptions on systems (3.1).
(A 1). S(t) is a fuzzy number satisfying for ( )i n
Ny E∈ '
( / ) ( ) ( : ( )i n
Nd dt S t y C I E∈ ,
'
( : ( ) )i n
NC I E∩ then,
( / ) ( ) [ ( ) ] ( ) ,d dt S t y A S t y S t Ay t I= = ∈
where,
1 1
[ ( )] [ ( )] [ ( ), ( )]
n n
i il ir
i i
S t S t S t S tα α α α
= =
= =∏ ∏
and ( )( , )ijS t j l rα
= is continuous with | ( ) |ijS t Cα
≤ , 0C > ,for all [0, ]t I T∈ =
(A2 ). The nonlinear fuzzy function :[0, ] ( ) ( )i n i n
N NF T E E× → and : ( ) ( )i n i n
N Ng E E→ is
continuous function and both are satisfied the global Lipschitz condtions, such that,
([ ( )] ,[ ( )] ) ([ ( )] ,[ ( )] )L Ld Fx s Fy s fd x s y sα α α α
≤
and
([ ( )] ,[ ( )] ) ([ (.)] ,[ (.)] )L Ld gx s gy s bd x yα α α α
≤
for all ( ), ( ), (.), (.) ( )i n
Nx s y s x y E∈ , f and b are a finite positive constants.
(A3 ) The fuzzy continuous function :[0, ] ( ) ( )i n i n
k N NG T E E× → is a strongly measurable
and satisfied the lipschitz condition, such that
([ ( )] ,[ ( )] ) ([ ( )] ,[ ( )] )L k k Ld G x s G y s gd x s y sα α α α
≤
for all ( ), ( ) ( )i n
Nx s y s E∈ and k=1, 2, … , n: g is positive constant.
7. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
33
N
(A4 ) The function : ( ) ( )i n i n
i N NI E E→ is a compact and there exist a positive
constant d such that
([ ( )] ,[ ( )] ) ([ (.)] ,[ (.)] )L i i Ld I x s I y s dd x yα α α α
≤
for all (.), (.) ( )i n
Nx y E∈
(A5). (1 ) (1 ) (1 ) (1 ) 1.cb T cT fT cT gT cT d cT+ + + + + + + + <
From Note 2.6 and hypotheses (A1), equation (3.1) can be expressed as
0
10 0 0
( ) ( )[ ( )] ( ) ( ) ( ) ( ) ( ) ( ) ( ),
t t tn
k k
k
x t S t x g x S t s Bu s ds S t s Fx s ds S t s G x s dW s
=
= − + − + − + −∑∫ ∫ ∫
( ) ( ) ( ) ( ( )),j j j j jx t x t x t I x t+ −
∆ = − =
0(0) ( ) (3.2)x g x x+ =
Theorem 3.1
Let T > 0, if hypotheses (A1 ) − (A2 ) are hold, then for every 0 ( )i n
Nx E∈ , equation (3.1)(u
≡ 0) have a unique fuzzy ([0, ]:( ) )i n
Nx C T E∈ .
Theorem 3.2
Condition (A1 ) − (A4 ) and (D) are satisfied. Then the system (3.1) is approximate
controllability on J.
Proof:
Let x˜β (·) be a fixed point of Φ and any fixed point of Φ is a mild solution of (3.1) on [0,
b]. By theorem 2.7, the control
* *
( ) ( ) ( , )[ ( )]a
ou t B S a t R P xβ β α
β= − Γ%% %
which satisfies
0
0
[ ( )] [ ( , )[ ( )][ ( )] ( ) ( )il
a
a
o il il ilx a x R x S a x g x S a s F x dsβ α α α β
α αβ β= − Γ − − − −∫%% %
1 10
( )( ) ( ) ( ) ( )( )( ( )),il il
an m
k il s k j j j
k j
S a s G x dW S S a t I x tα α β α −
= =
− − − −∑ ∑∫ %
0
0
( )[ ( )] ( ) ( ) (3.3)il ir
a
ir irx S a x g x S a s F x dsα α α β
α − − − −∫ %
1 10
( )( ) ( ) ( ) ( )( )( ( ))]ir
an m
ir k ir s k j j j
k j
S a s G x dW S S a t I x tα α β α −
= =
− − − −∑ ∑∫ %
where,
8. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
34
0
0
1 10
0
0
0
[ ( )] [ ( )][ ( )] ( ) ( )
( )( ) ( ) ( ) ( )( )( ( )),
( )[ ( )] ( ) ( )
( )( ) ( ) ( )
il
il il
ir ir
a
il il il s
an m
k il s k j j j
k j
a
ir ir
a
ir k ir s k
P x x S a x g x S a s F x ds
S a s G x dW S S a t I x t
x S a x g x S a s F x ds
S a s G x dW S
β α α α β
α
α α β α
α α α β
α
α α β
−
= =
= − − − −
− − − −
− − − −
− −
∫
∑ ∑∫
∫
∫
% %
%
%
%
1 1
( )( )( ( ))]ir
n m
j j j
k j
S a t I x tα −
= =
− −∑ ∑
By (A2) −(A4 )
([ ] ,[ ( )] ) , ([( ) ] ,[( )( )] )
([ ] ,[ ( )] )
L s L L k s k L
L s L
d Fx F s fd d G x G s gd
d gx g s bd
β α α β α α
β α α
≤ ≤
≤
% %
%
Here, the sequence ( ),( ) ( ) ( )il s k il s il sF x G x and g xα β α β α β
% % % are bounded in ( )i n
NE . And
( ),( ) ( ) ( )il k il ilF s G s and g sα α α
are all weakly convergent subsequence that are bounded in
( )i n
NE , respectively. Take
0
0
1 10
0
0
1 0
[ ( )][ ( )] ( ) ( )
( )( ) ( ) ( ) ( )( )( ( )),
( )[ ( )] ( ) ( )
( )( ) ( ) ( ) ( )(
il
il il
ir ir
ir
a
il il il
an m
k il k j j j
k j
a
ir ir
an
ir k ir k j
k
x S a x g x S a s F s ds
S a s G s dW S S a t I x t
x S a x g x S a s F s ds
S a s G s dW S S a t
α α α
α
α α α
α α α
α
α α α
ω
−
= =
=
= − − − −
− − − −
− − − −
− − − −
∫
∑ ∑∫
∫
∑∫
%
1
)( ( ))].
m
j j
j
I x t−
=
∑
It follows by the compactness of the operators
0
(.) (., ) ( ) :
a
q U s q s ds→ ∫
2
( , ) ( , ),L J X C J X→ we obtain that
0
1 0
||[ ( )] || ( )[ ( ), ( )]
( )[( ) ( ),( ) ( )] ( ) 0 0
ij
il
a
ij s ij
an
k il s k il k
k
P x S a s F x F s ds
S a s G x G s dW S as
γ α α α β α
α α β α
ω
β +
=
− ≤ −
+ − → →
∫
∑∫
%% %
%
where, j = l, r. By Definition
9. International Journal of Fuzzy Logic Systems (IJFLS) Vol.5, No.4, October 2015
35
||[ ( )] || ( , )[ ( )]
( , )([ ( )] )
a
o
a
o
x a x R P x
R P x
γ α β α
α
β α
β β
β β ω ω
− = Γ
= Γ − +
%% %
% % %%
( , ) ( , )[ ( )]
( , ) [ ( )] 0 0
a a
o o
a
o
R R P x
R P x as
β α
β α
β β ω β β ω
β β ω ω β +
≤ Γ + Γ −
≤ Γ + − → →
% %% %%
% % %%
ie., ||[ ( )] || 0x a xγ α
α− →% . ie., this proves the approximate controllability of (3.1).
4. CONCLUSION
The article addresses the approximate controllability results for impulsive linear fuzzy stochastic
differential equations with nonlocal conditions in Banach space. By using stochastic analysis,
fuzzy process, fuzzy solution, Banach fixed point theorems and some sufficient conditions for the
approximate controllability of the linear fuzzy stochastic control system are formulated and
proved under the assumptions that are related linear system is approximate controllable.
ACKNOWLEDGMENTS
The authors would like to thank Dr.K.Balachandran, Professor and Head, Department of
Mathematics Bharathiar University for lending his support to complete this article.
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