• 대한전기학회논문지
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• 제38권9호
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• pp.753-760
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• 1989

A method is suggested to design a stochastic observer which can be used as a state estimator for the optimal control of a one link flexible manipulator. This stochastic observer is derived from unifying the two concepts of reduced-state deterministic observer theory and optimal Kalman filtering theory. In estimating state variables for the optimal control, instead of using the two different state estimators for the deterministic system with noise free measurements and stochastic system with noise measurements, only one stochastic observer is designed which is to be used in both systems commonly. Through the simulation, it has been shown that the flexible system with the stochastic observer is similar in characteristics to the flexible system assuming that all states can be measured.

• 호남수학학술지
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• 제44권3호
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• pp.402-418
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• 2022

Noise is a fundamental factor to increased validity and regularity of spike propagation and neuronal firing in the nervous system. In this paper, we examine the stochastic version of the Izhikevich-FitzHugh neuron dynamical model. This approach is based on techniques presented by Luo and Guo, which provide a general framework for the bifurcation and stability analysis of two dimensional stochastic dynamical system as an Itô averaging diffusion system. By using largest lyapunov exponent, local and global stability of the stochastic system at the equilibrium point are investigated. We focus on the two kinds of stochastic bifurcations: the P-bifurcation and the D-bifurcations. By use of polar coordinate, Taylor expansion and stochastic averaging method, it is shown that there exists choices of diffusion and drift parameters such that these bifurcations occurs. Finally, numerical simulations in various viewpoints, including phase portrait, evolution in time and probability density, are presented to show the effects of the diffusion and drift coefficients that illustrate our theoretical results.

• Journal of applied mathematics & informatics
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• 제25권1_2호
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• pp.183-199
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• 2007

In this paper we research the problem in which the objective is to minimize the sum of squared deviations of job expected completion times from the due date, and the job processing times are stochastic. In the problem the machine is subject to stochastic breakdowns and all jobs are preempt-repeat. In order to show that the replacing ESSD by SSDE is reasonable, we discuss difference between ESSD function and SSDE function. We first give an express of the expected completion times for both cases without resampling and with resampling. Then we show that the optimal sequence of the problem V-shaped with respect to expected occupying time. A dynamic programming algorithm based on the V-shape property of the optimal sequence is suggested. The time complexity of the algorithm is pseudopolynomial.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권1호
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• pp.19-30
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• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1993년도 봄 학술발표회논문집
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• pp.117-124
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• 1993

The Neumann Expansion method has been used for evaluating the response variability of three dimensional truss structure resulting from the spatial variability of material properties with the aid of the finite element method, and in conjunction with the direct Monte Carlo simulation methods. The spatial variabilites are modeled as three-dimensional stochastic field. Yamazaki 〔1〕 has extended the Neumann Expansion method to the plane-strain problem to obtain the response variability of 2 dimensional stochastic systems. This paper presents the extension of the Neumann Expansion method to 3 dimensional stochastic systems. The results by the NEM are compared with those by the deterministic finite element analysis and by the direct Monte Carlo simulation method

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1089-1091
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• 1996

This paper presents a design method of Kalman Filter on continuous nonlinear stochastic system via BPF(Block Pulse Function). When we design Kalman Filter on nonlinear stochastic system, we must linearize this systems. In this paper, we uses the adaptive approach scheme and BPF for linearizing of nonlinear system and solving the Riccati differential equation which is usually guite difficult. This method proposed in this paper is simple and have computational advantages. Furthermore this method is very applicable to analysis and design of Kalman Filter on nonlinear stochastic systems.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.139-144
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• 1993

In this paper, a robust reduced order adaptive controller is proposed based on Internal Model Control(IMC) structure for stochastic linear stable systems. The concept of gain margin is utilized to make the adaptive IMC controller robust. We prove the stability of the proposed adaptive IMC system for stable plants under the assumption that upper bounds for system orders are known. Simulation results show that the proposed method has good performance and stability robustness.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.159.1-159
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• 2001

A new time-domain FIR parameter estimation called the receding horizon least square estimation (RHLSE) is suggested for stochastic systems by combining the well known least square estimation with the receding horizon strategy. It can be always obtained without the requirement of any \textit{a priori} information about the horizon initial parameter. A fast algorithm for the suggested estimation is also presented which is remarkable in the view of computational advantage and simple implementation. It is shown that the proposed estimation is robust against temporary modeling uncertainties due to their FIR structure through simulation studies.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제21권4호
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• pp.215-224
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• 2017

The moment closure method is an approximation method to compute the moments for stochastic models of chemical reaction systems. In this paper, we develop an analytic estimation of errors generated from the approximation of an infinite system of differential equations into a finite system truncated by the moment closure method. As an example, we apply the result to an essential bimolecular reaction system, the dimerization model.