• 제목/요약/키워드: Stochastic systems

검색결과 766건 처리시간 0.029초

A Stochastic Model for Order Book Dynamics: An Application to Korean Stock Index Futures

  • Lee, Yongjae;Kim, Woo Chang
    • Management Science and Financial Engineering
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    • 제19권1호
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    • pp.37-41
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    • 2013
  • This study presents an application of stochastic model for limit order book (LOB) dynamics to Korean Stock Index Futures (KOSPI 200 Futures). Since KOSPI 200 futures market is widely known as one of the most liquid markets in the world, direct application of an existing model is hardly possible. Therefore, we modified an existing model to successfully model and predict the dynamics of extremely liquid KOSPI 200 futures market.

확률적 이선형시스템의 최적제 (Optimal Control of Stochastic Bilinear Systems)

  • Hwang, Chun-Sik
    • 대한전기학회논문지
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    • 제31권7호
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    • pp.18-24
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    • 1982
  • We derived an optimal control of the Stochastic Bilinear Systems. For that we, firstly, formulated stochastic bilinear system and estimated its state when the system state is not directly observable. Optimal control problem of this system is reviewed on the line of three optimization techniques. An optimal control is derived using Hamilton-Jacobi-Bellman equation via dynamic programming method. It consists of combination of linear and quadratic form in the state. This negative feedback control, also, makes the system stable as far as value function is chosen to be a Lyapunov function. Several other properties of this control are discussed.

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Comparison of uniform and spatially varying ground motion effects on the stochastic response of fluid-structure interaction systems

  • Bilici, Yasemin;Bayraktar, Alemdar;Adanur, Suleyman
    • Structural Engineering and Mechanics
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    • 제33권4호
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    • pp.407-428
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    • 2009
  • The effects of the uniform and spatially varying ground motions on the stochastic response of fluid-structure interaction system during an earthquake are investigated by using the displacement based fluid finite elements in this paper. For this purpose, variable-number-nodes two-dimensional fluid finite elements based on the Lagrangian approach is programmed in FORTRAN language and incorporated into a general-purpose computer program SVEM, which is used for stochastic dynamic analysis of solid systems under spatially varying earthquake ground motion. The spatially varying earthquake ground motion model includes wave-passage, incoherence and site-response effects. The effect of the wave-passage is considered by using various wave velocities. The incoherence effect is examined by considering the Harichandran-Vanmarcke and Luco-Wong coherency models. Homogeneous medium and firm soil types are selected for considering the site-response effect where the foundation supports are constructed. A concrete gravity dam is selected for numerical example. The S16E component recorded at Pacoima dam during the San Fernando Earthquake in 1971 is used as a ground motion. Three different analysis cases are considered for spatially varying ground motion. Displacements, stresses and hydrodynamic pressures occurring on the upstream face of the dam are calculated for each case and compare with those of uniform ground motion. It is concluded that spatially varying earthquake ground motions have important effects on the stochastic response of fluid-structure interaction systems.

Differential Geometric Conditions for the state Observation using a Recurrent Neural Network in a Stochastic Nonlinear System

  • Seok, Jin-Wuk;Mah, Pyeong-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.592-597
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    • 2003
  • In this paper, some differential geometric conditions for the observer using a recurrent neural network are provided in terms of a stochastic nonlinear system control. In the stochastic nonlinear system, it is necessary to make an additional condition for observation of stochastic nonlinear system, called perfect filtering condition. In addition, we provide a observer using a recurrent neural network for the observation of a stochastic nonlinear system with the proposed observation conditions. Computer simulation shows that the control performance of the stochastic nonlinear system with a observer using a recurrent neural network satisfying the proposed conditions is more efficient than the conventional observer as Kalman filter

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CONTROLLABILITY OF STOCHASTIC FUNCTIONAL INTEGRODIFFERENTIAL EVOLUTION SYSTEMS

  • Kokila, J.;Balachandran, K.
    • Journal of applied mathematics & informatics
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    • 제29권3_4호
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    • pp.587-601
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    • 2011
  • In this paper, we prove the existence and uniqueness of mild solution for stochastic functional integrodifferential evolution equations and derive sufficient conditions for the controllability results. As an illustration we consider the controllability for a system governed by a random motion of a string.

On procedures for reliability assessment of mechanical systems and structures

  • Schueller, G.I.
    • Structural Engineering and Mechanics
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    • 제25권3호
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    • pp.275-289
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    • 2007
  • In this paper a brief overview of methods to assess the reliability of mechanical systems and structures is presented. A selection of computational procedures, stochastic structural dynamics, stochastic fatigue crack growth and reliability based optimization are discussed. It is shown that reliability based methods may form the basis for a rational decision making.

관측자의 선형확률연속시스템에의 적용 (An application of observer to the linear stochastic contimuous systems)

  • 고명삼;홍석교
    • 전기의세계
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    • 제24권5호
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    • pp.103-106
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    • 1975
  • This Paper deals with an applicatoin of Luenberger Observer to the Linear Stochastic Systems. The basic technique is the use of a matrix version of the Maximum Principle of Pontryagin coupled with the use of gradient matrices to derive the gain matix for minimum error covariance. The optimal observer which is derived turns out to be identical to the well-known Kalman-Bucy Filter.

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(s, S) 재고관리 시스템에 대한 확률최적화 기법의 응용 (Application of Stochastic Optimization Method to (s, S) Inventory System)

  • Chimyung Kwon
    • 한국시뮬레이션학회논문지
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    • 제12권2호
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    • pp.1-11
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    • 2003
  • In this paper, we focus an optimal policy focus optimal class of (s, S) inventory control systems. To this end, we use the perturbation analysis and apply a stochastic optimization algorithm to minimize the average cost over a period. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. Our simulation results indicate that the optimal estimates of s and S obtained from a stochastic optimization algorithm are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and review period. Another directions involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

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Stability and Robust H Control for Time-Delayed Systems with Parameter Uncertainties and Stochastic Disturbances

  • Kim, Ki-Hoon;Park, Myeong-Jin;Kwon, Oh-Min;Lee, Sang-Moon;Cha, Eun-Jong
    • Journal of Electrical Engineering and Technology
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    • 제11권1호
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    • pp.200-214
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    • 2016
  • This paper investigates the problem of stability analysis and robust H controller for time-delayed systems with parameter uncertainties and stochastic disturbances. It is assumed parameter uncertainties are norm bounded and mean and variance for disturbances of them are known. Firstly, by constructing a newly augmented Lyapunov-Krasovskii functional, a stability criterion for nominal systems with time-varying delays is derived in terms of linear matrix inequalities (LMIs). Secondly, based on the result of stability analysis, a new controller design method is proposed for the nominal form of the systems. Finally, the proposed method is extended to the problem of robust H controller design for a time-delayed system with parameter uncertainties and stochastic disturbances. To show the validity and effectiveness of the presented criteria, three examples are included.

Frequency-Domain Balanced Stochastic Truncation for Continuous and Discrete Time Systems

  • Shaker, Hamid Reza
    • International Journal of Control, Automation, and Systems
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    • 제6권2호
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    • pp.180-185
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    • 2008
  • A new method for relative error continuous and discrete time model order reduction is proposed. The reduction technique is based on two recently developed methods, namely frequency domain balanced truncation within a frequency bound and inner-outer factorization techniques. The proposed method is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency. Numerical results show the accuracy and efficiency enhancement of the method.