• 대한기계학회논문집
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• 제19권3호
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• pp.697-704
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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 the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. 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 and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• 대한기계학회논문집
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• 제14권6호
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• pp.1426-1435
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• 1990

본 연구에서는 확률론적 등가선형화 기법을 사용하여 비선형 랜덤 시스템을 선형화하였다.또 이 선형화된 시스템을 최근에 새로이 제안된 방법을 적용하여 비 백색잡음형태의 랜덤 가진을 받을 때 그 거동을 구하였다.

• Structural Engineering and Mechanics
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• 제64권2호
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• pp.259-270
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• 2017

The stochastic vibration response of the sandwich beam with the nonlinear adjustable visco-elastomer core and supported mass under stochastic support motion excitations is studied. The nonlinear dynamic properties of the visco-elastomer core are considered. The nonlinear partial differential equations for the horizontal and vertical coupling motions of the sandwich beam are derived. An analytical solution method for the stochastic vibration response of the nonlinear sandwich beam is developed. The nonlinear partial differential equations are converted into the nonlinear ordinary differential equations representing the nonlinear stochastic multi-degree-of-freedom system by using the Galerkin method. The nonlinear stochastic system is converted further into the equivalent quasi-linear system by using the statistic linearization method. The frequency-response function, response spectral density and mean square response expressions of the nonlinear sandwich beam are obtained. Numerical results are given to illustrate new stochastic vibration response characteristics and response reduction capability of the sandwich beam with the nonlinear visco-elastomer core and supported mass under stochastic support motion excitations. The influences of geometric and physical parameters on the stochastic response of the nonlinear sandwich beam are discussed, and the numerical results of the nonlinear sandwich beam are compared with those of the sandwich beam with linear visco-elastomer core.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.156-161
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• 1994

In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

• Structural Engineering and Mechanics
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• 제3권3호
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• pp.273-287
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• 1995

Stochastic response of systems to random excitation can be estimated by direct integration methods in the time domain such as the stochastic central difference method (SCDM). In this paper, the SCDM is applied to compute the variance and covariance in response of linear and nonlinear structures subjected to random excitation. The accuracy of the SCDM is assessed using two-DOF systems with both deterministic and random material properties excited by white noise. For the former case, closed-form solutions can be obtained. Numerical results also are presented for a simply supported geometrically nonlinear beam. The stiffness of this beam is modeled as a random field, and the beam is idealized by the stochastic finite element method. A perturbation technique is applied to formulate the equations of motion of the system, and the dynamic structural response statistics are obtained in a time domain analysis. The effect of variations in structural parameters and the numerical stability of the SCDM also are examined.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 춘계학술대회논문집
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• pp.892-896
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• 2001

백색잡음 불규칙 과정으로 모델링된 난류형태의 유체운동에 의하여 가진되는 비선형 시스템의 특성과 제어기법에 대해 연구하였다. 고려된 물리적인 모델은 주질량과 끝단 집중질량을 갖는 보형태의 구조물이다. 그 지배방정식은 확률론적 관점에서 F-P-K 접근법으로 유도되었고, 비선형 해석법으로 Gaussian Closure방법을 이용하였다. 비선형 시스템의 제어기법으로는 슬라이딩 모드 제어기를 최초로 확률영역에서 설계하고 그 효과를 확률영역 및 시간영역에서 고찰하였다.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.391-399
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• 2006

In order to solve the optimization problem of designing the trajectory of three-dimensional horizontal well, we establish a multi-phase, nonlinear, stochastic dynamic system of the trajectory of horizontal well. We take the precision of hitting target and the total length of the trajectory as the performance index. By the integration of the state equation, this model can be transformed into a nonlinear stochastic programming. We discuss here the necessary conditions under which a local solution exists and depends in a continuous way on the parameter (perturbation). According to the properties we propose a revised Hooke-Jeeves algorithm and work out corresponding software to calculate the local solution of the nonlinear stochastic programming and the expectancy of the performance index. The numerical results illustrate the validity of the proposed model and algorithm.

• 한국농공학회지
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• 제36권1호
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• pp.54-62
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• 1994

The expanding technique of the Stochastic Finite Element Method(SFEM) is proposed in this paper for adapting direct integration methods in stochastical dynamic analysis of structures. Grafting the direct integration methods and the SFEM together, one can deal with nonlinear structures and nonstationary process problems without any restriction. The stochastical central diffrence and stochastic Houbolt methods are introduced to show the expanding technique, and their adaptabilities are discussed. Results computed by the proposed method (the Stochastic Finite Element Method in Dynamics: SFEMD) for two degree-of-free- dom system are compared with those obtained by Monte Carlo Simulation.

• Structural Engineering and Mechanics
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• 제18권1호
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• pp.125-135
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• 2004

Industrial structure systems may have nonlinearity, and are also sometimes exposed to the danger of random excitation. This paper proposes a method to analyze response and reliability design of a complex nonlinear structure system under random excitation. The nonlinear structure system which is subjected to random process is modeled by finite element method. The nonlinear equations are expanded sequentially using the perturbation theory. Then, the perturbed equations are solved in probabilistic methods. Several statistical properties of random process that are of interest in random vibration applications are reviewed in accordance with the nonlinear stochastic problem.

• 대한수학회보
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• 제55권2호
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• pp.479-497
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• 2018

This paper deals with an optimal control on semilinear stochastic functional differential equations with Poisson jumps in a Hilbert space. The existence of an optimal control is derived by the solution of proposed system which satisfies weakly sequentially compactness. Also the stochastic maximum principle for the optimal control is established by using spike variation technique of optimal control with a convex control domain in Hilbert space. Finally, an application of retarded type stochastic Burgers equation is given to illustrate the theory.