• 제목/요약/키워드: stochastic differential system

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EXISTENCE UNIQUENESS AND STABILITY OF NONLOCAL NEUTRAL STOCHASTIC DIFFERENTIAL EQUATIONS WITH RANDOM IMPULSES AND POISSON JUMPS

  • CHALISHAJAR, DIMPLEKUMAR;RAMKUMAR, K.;RAVIKUMAR, K.;COX, EOFF
    • Journal of Applied and Pure Mathematics
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    • 제4권3_4호
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    • pp.107-122
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    • 2022
  • This manuscript aims to investigate the existence, uniqueness, and stability of non-local random impulsive neutral stochastic differential time delay equations (NRINSDEs) with Poisson jumps. First, we prove the existence of mild solutions to this equation using the Banach fixed point theorem. Next, we demonstrate the stability via continuous dependence initial value. Our study extends the work of Wang, and Wu [16] where the time delay is addressed by the prescribed phase space 𝓑 (defined in Section 3). To illustrate the theory, we also provide an example of our methods. Using our results, one could investigate the controllability of random impulsive neutral stochastic differential equations with finite/infinite states. Moreover, one could extend this study to analyze the controllability of fractional-order of NRINSDEs with Poisson jumps as well.

HYERS-ULAM STABILITY OF FRACTIONAL STOCHASTIC DIFFERENTIAL EQUATIONS WITH RANDOM IMPULSE

  • Dumitru Baleanu;Banupriya Kandasamy;Ramkumar Kasinathan;Ravikumar Kasinathan;Varshini Sandrasekaran
    • 대한수학회논문집
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    • 제38권3호
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    • pp.967-982
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    • 2023
  • The goal of this study is to derive a class of random impulsive non-local fractional stochastic differential equations with finite delay that are of Caputo-type. Through certain constraints, the existence of the mild solution of the aforementioned system are acquired by Kransnoselskii's fixed point theorem. Furthermore through Ito isometry and Gronwall's inequality, the Hyers-Ulam stability of the reckoned system is evaluated using Lipschitz condition.

확률적 동적계의 해석에 관한 연구 (A Study on the Analysis of Stochastic Dynamic System)

  • 남성현;김호룡
    • 한국정밀공학회지
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    • 제12권4호
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    • pp.127-134
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    • 1995
  • The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents a generalized stochastic model of dynamic system subjected to bot external and parametric nonstationary stochastic input. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method. But the second moment equation is founded to constitute an infinite coupled set of differential equations, so this equations are numerically evaluated by cumulant neglect closure method and Runge-Kutta method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

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EXISTENCE AND STABILITY RESULTS FOR STOCHASTIC FRACTIONAL NEUTRAL DIFFERENTIAL EQUATIONS WITH GAUSSIAN NOISE AND LÉVY NOISE

  • P. Umamaheswari;K. Balachandran;N. Annapoorani;Daewook Kim
    • Nonlinear Functional Analysis and Applications
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    • 제28권2호
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    • pp.365-382
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    • 2023
  • In this paper we prove the existence and uniqueness of solution of stochastic fractional neutral differential equations with Gaussian noise or Lévy noise by using the Picard-Lindelöf successive approximation scheme. Further stability results of nonlinear stochastic fractional dynamical system with Gaussian and Lévy noises are established. Examples are provided to illustrate the theoretical results.

STABILITY OF THE MILSTEIN METHOD FOR STOCHASTIC DIFFERENTIAL EQUATIONS WITH JUMPS

  • Hu, Lin;Gan, Siqing
    • Journal of applied mathematics & informatics
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    • 제29권5_6호
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    • pp.1311-1325
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    • 2011
  • In this paper the Milstein method is proposed to approximate the solution of a linear stochastic differential equation with Poisson-driven jumps. The strong Milstein method and the weak Milstein method are shown to capture the mean square stability of the system. Furthermore using some technique, our result shows that these two kinds of Milstein methods can well reproduce the stochastically asymptotical stability of the system for all sufficiently small time-steps. Some numerical experiments are given to demonstrate the conclusions.

ESTIMATION OF NON-INTEGRAL AND INTEGRAL QUADRATIC FUNCTIONS IN LINEAR STOCHASTIC DIFFERENTIAL SYSTEMS

  • Song, IL Young;Shin, Vladimir;Choi, Won
    • Korean Journal of Mathematics
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    • 제25권1호
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    • pp.45-60
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    • 2017
  • This paper focuses on estimation of an non-integral quadratic function (NIQF) and integral quadratic function (IQF) of a random signal in dynamic system described by a linear stochastic differential equation. The quadratic form of an unobservable signal indicates useful information of a signal for control. The optimal (in mean square sense) and suboptimal estimates of NIQF and IQF represent a function of the Kalman estimate and its error covariance. The proposed estimation algorithms have a closed-form estimation procedure. The obtained estimates are studied in detail, including derivation of the exact formulas and differential equations for mean square errors. The results we demonstrate on practical example of a power of signal, and comparison analysis between optimal and suboptimal estimators is presented.

EXISTENCE AND UNIQUENESS RESULT FOR RANDOM IMPULSIVE STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS WITH FINITE DELAYS

  • DIMPLEKUMAR, CHALISHAJAR;K., RAMKUMAR;K., RAVIKUMAR
    • Journal of Applied and Pure Mathematics
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    • 제4권5_6호
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    • pp.233-247
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    • 2022
  • This manuscript addressed, the existence and uniqueness result for random impulsive stochastic functional differential equations with finite time delays. The study of random impulsive stochastic system is a new area of research. We interpret the meaning of a stochastic derivative and how it differs from the classical derivative. We prove the existence and uniqueness of mild solutions to the equations by using the successive approximation method. We conclude the article with some interesting future extension. This work extends the work of [18, 12, 20]. Finally, an example is given to illustrate the theoretical result.

Semi-active bounded optimal control of uncertain nonlinear coupling vehicle system with rotatable inclined supports and MR damper under random road excitation

  • Ying, Z.G.;Yan, G.F.;Ni, Y.Q.
    • Coupled systems mechanics
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    • 제7권6호
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    • pp.707-729
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    • 2018
  • The semi-active optimal vibration control of nonlinear torsion-bar suspension vehicle systems under random road excitations is an important research subject, and the boundedness of MR dampers and the uncertainty of vehicle systems are necessary to consider. In this paper, the differential equations of motion of the coupling torsion-bar suspension vehicle system with MR damper under random road excitation are derived and then transformed into strongly nonlinear stochastic coupling vibration equations. The dynamical programming equation is derived based on the stochastic dynamical programming principle firstly for the nonlinear stochastic system. The semi-active bounded parametric optimal control law is determined by the programming equation and MR damper dynamics. Then for the uncertain nonlinear stochastic system, the minimax dynamical programming equation is derived based on the minimax stochastic dynamical programming principle. The worst-case disturbances and corresponding semi-active bounded parametric optimal control are obtained from the programming equation under the bounded disturbance constraints and MR damper dynamics. The control strategy for the nonlinear stochastic vibration of the uncertain torsion-bar suspension vehicle system is developed. The good effectiveness of the proposed control is illustrated with numerical results. The control performances for the vehicle system with different bounds of MR damper under different vehicle speeds and random road excitations are discussed.

가관측적인 랜덤 학수를 가진 스토캐스틱 시스템의 최적제어 (Optimal Control of Stochastic Systems with Completely Observable Random Coefficients)

  • 이만형;황창선
    • 대한전기학회논문지
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    • 제34권5호
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    • pp.173-178
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    • 1985
  • The control of a linear system with random coefficients is discussed here. The cost function is of a quadratic form and the random coefficients are assumed to be completely observable by the controller. Stochastic Process involved in the problem by the controller. Stochastic Process involved in the problem formulation is presented to be the unique strong solution to the corresponding stochastic differential equations. Condition for the optimal control is represented through the existence of solution to a Cauchy problem for the given nonlinear partial differential equation. The optimal control is shown to be a linear function of the states and a nonlinear function of random parameters.

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Solution of randomly excited stochastic differential equations with stochastic operator using spectral stochastic finite element method (SSFEM)

  • Hussein, A.;El-Tawil, M.;El-Tahan, W.;Mahmoud, A.A.
    • Structural Engineering and Mechanics
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    • 제28권2호
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    • pp.129-152
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    • 2008
  • This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.