• Journal of Ubiquitous Convergence Technology
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• v.2 no.2
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• pp.105-110
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• 2008

The definition of the program control is introduced on the theory of the basis of the first integrals SDE system. That definition allows constructing the program control gives opportunity to stochastic system to remain on the given dynamic variety. The program control is considered in terms of dynamically invariant for stochastic process.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1292-1297
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• 2000

For dynamic system under the external irregular disturbance, a performance of the controller designed by using of the 'Heo-stochastic control methodology' is investigated by simulations and experiments. MIMO Flexible cantilever beam, sticked with piezoceramics used as a sensor and actuator, under the irregular disturbance at bottom is modelled in physical domain. Dynamic moment equation about the system is derived through both the Ito's stochastic differential equation and Fokker-Planck-Kolmogoroff equation and also system's characteristics in stochastic domain is analyzed. In this study, the controller suppresses the amplitude of the system's moment response to the external disturbance. MIMO PI controller('Heo-stochastic MIMO PI controller') is designed in the stochastic domain and the response characteristics are investigated in the time domain

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2007-2013
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• 1999

A Newly proposed control methodology applied to the aeroelastic system experiencing flutter is investigated and its performance is verified experimentally. The flexible cantilever beam slicked with piezofilm sensor and piezoceramic actuator is modelled in physical domain. Dynamic moment equation for the system is derived via Ito's stochastic differential equation and F-P-K equation. Also system's characteristics in stochastic domain is analyzed simultaneously. LQG controller is designed and used in physical and stochastic domain. It is shown experimentally that the vibration of beam is controlled effectively by designed LQG controller in physical domain. By comparing the result with that of LQG controller designed in stochastic domain, it is shown that the new control method, called Heo-stochastic control technique, has better performance as a controller.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.354-359
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• 2006

The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.

• Wind and Structures
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• v.10 no.1
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• pp.45-60
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• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.197-200
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• 2007

Dynamic power management reduces the power consumption of the system by switching system components into different power states, which have different power consumption levels. The main function of a power management is to decide when to perform state transitions. In this paper, a power management model based on stochastic processes is introduced. This model is developed using SRN (Stochastic Reward Nets), which has facilities to represent system queue and various modeling functions.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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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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• v.20 no.4
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• pp.389-403
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• 2005

In the present paper it is aimed to perform the stochastic dynamic analysis of fluid and fluidstructure systems by using the Lagrangian approach. For that reason, variable-number-nodes twodimensional isoparametric fluid finite elements are programmed in Fortran language by the authors and incorporated into a general-purpose computer program for stochastic dynamic analysis of structure systems, STOCAL. Formulation of the fluid elements includes the effects of compressible wave propagation and surface sloshing motion. For numerical example a rigid fluid tank and a dam-reservoir interaction system are selected and modeled by finite element method. Results obtained from the modal analysis are compared with the results of the analytical and numerical solutions. The Pacoima Dam record S16E component recorded during the San Fernando Earthquake in 1971 is used as a ground motion. The mean of maximum values of displacements and hydrodynamic pressures are compared with the deterministic analysis results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.10
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• pp.918-922
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• 2007

Most of the study on system identification has been carried out using input/output relation in physical domain. However identification concept of stochastic system has not been reported up to now. Interest is focused to identify an unknown dynamic system under random external disturbances which is not possible to measure. A concept to identify the system parameters in stochastic domain is proposed and implemented in terms of simulation. Attempt has been made to identify the system parameters in inverse manner in stochastic domain based on system output only. Simulation is conducted to reveal quite noticeable performance of the proposed concept.

• Bulletin of the Korean Mathematical Society
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• v.53 no.1
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• pp.103-117
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• 2016

Abstract. In this paper, we study a modified stochastic predator-prey system with general ratio-dependent functional response. We prove that the system has a unique positive solution for given positive initial value. Then we investigate the persistence and extinction of this stochastic system. At the end, we give some numerical simulations, which support our theoretical conclusions well.