• Journal of the Korean Society for Precision Engineering
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• v.6 no.1
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• pp.33-44
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• 1989

A controller disign method is proposed for multivariable nonlinear stochastic systems with hard nonlinearities such as Coulomb friction, backlash and saturation. In order to take the nonlinearities into account statistical linearization techniques are used. And multi- variable pole placement techniques are applied to design controller for the statistically linearized multivariable systems. The basic concept of the controller design method is to solve two coupled equations, characteristic equation and Lyapunov equation, simultaneously and iteratively for statistically linearized multivariable stochastic systems. An aircraft with saturation serves as a design example. The design example illustrates the influence of nonlinear effects. The results of the analysis are compared to Monte Carlo simulation to test their accuracy.

• Magazine of the Korean Society of Agricultural Engineers
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• v.34 no.1
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• pp.100-106
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• 1992

The objective of this study is to develop a real-time runoff forecasting model considering stochastic component. The model is composed of deterministic and stochastic components. Simplified tank model was selected as a deterministic runoff forecasting model. The time series of estimation residual resulting from the tank model simulation was analyzed and was best suited to the second-order autoregressive model. ARTANK model which combined the tank model with the autoregressive process was developed. And it was applied to a BANWEOL basin for validation. The simulation results showed a good agreement with the observed field data.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.129-134
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• 2003

In this paper, we determine optimal reduction in the lead time and setup cost for some stochastic inventory models. And we propose more general model that allow the backorder rate as a control variable. We first assume that the lead time demand follows a normal distribution. And we assume that the backorder rate is dependent on the length of lead time through the amount of shortages. The stochastic models analyzed in this paper are the classical continuous and periodic review policy models with a mixture of backorders and lost sales. For each of these models, we provide a sufficient conditions for the uniqueness of the optimal operating policy. We also develop algorithms for solving these models and provide illustrative numerical examples.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.107-116
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• 1996

In the stochastic structure for doing exact calculationk, an input number must be changed to a pulse stream. Because the performance of random number generator (RNG) is controlled by its initial condition, we suggested newly modified cellular automata (MCA) which is uses a counter for boundary condition. We compared newly suggested MCA RNG to previously reported RNGs using the AND gate passing outputs which have the same meaning of multiplication in the stochastic calculation. In order to use stochastic we studied about the method, one large RNG can generate many small random numbers. In this method, RNG must have large drive capabilities for many input comparator. So we studied about drive capabilities using BiCMOS circuit and CMOS circit by SPICE.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.237-247
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• 2023

Fourier series-based models in the time domain are frequently established to represent individual bouncing loads, which neglects the stochastic property of human bouncing activity. A power spectral density (PSD) model in the frequency domain for individual bouncing loads is developed herein. An experiment was conducted on individual bouncing loads, resulting in 957 records linked to form long samples to achieve a fine frequency resolution. The Welch method was applied to the linked samples to obtain the experimental PSD, which was normalized by the bouncing frequency and the harmonic order. The energy, energy distribution center, and energy distribution shape of the experimental PSD were investigated to establish the PSD model. The proposed model was used to analyze structural vibration responses using stochastic vibration theory, which was verified via field measurements. It is believed that this framework can evaluate the vibration capacity of structures excited by bouncing crowds, such as concert halls and grandstands.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.166-168
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• 2015

Line of Balance (LOB) method is suitable to schedule construction projects composed of repetitive activities. Since existing LOB based repetitive project scheduling methods are deterministic, they do not lend themselves to handle uncertainties involved in repetitive construction process. Indeed, existing LOB scheduling dose not handle variability of project performance indicators. In order to bridge the gap between reality and estimation, this study provides a stochastic LOB based scheduling method that allows schedulers for effectively dealing with the uncertainties of a construction project performance. The proposed method retrieves an appropriate probability distribution function (PDF) concerning project completion times, and determines favorable start times of activities. A case study is demonstrated to verify and validate the capability of the proposed method in a repetitive construction project planning.

• Geotechnical Engineering
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• v.4 no.3
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• pp.19-26
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• 1988

A stochastic numerical model for predictions of differential settlement of foundation Eoils is developed in this Paper. The differential settlement is highly dependent on the spatial variability of elastic modulus of soil. The Kriging method is used to account for the spatial variability of the elastic modulus. This technique provides the best linear unbiased estimator of a parameter and its minimum variance from a limited number of measured data. The stochastic finite element method, employing the first-order second-moment analysis for computations of error Propagation, is used to obtain the means, ariances, and covariances of nodal displacements. Finally, a reliability model of differential settlement is proposed by using the results of the stochastic FEM analysis. It is found that maximum differential settlement occurs when the distance between two foundations is approximately same It with the scale of fluctuation in horizontal direction, and the probability that differential settlement exceeds the allot.able vague might be significant.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.385-395
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• 2002

A stochastic model using FOEA(First-Order Error-Analysis) and Monte Carlo Method is developed to predict water quality variation in a river. A sensitivity analysis using influential matrix is performed to determine the significant reaction coefficients. Also the BFGS (Broyden-Fletcher-Goldfarb-Shanno) optimization method is applied to estimate the optimal values of the major reaction coefficients. The developed stochastic model is applied to the real study reach and the results are agreed well with those of deterministic analysis. The process for analyzing the uncertainties of the discharge, water quality and reaction coefficients of headwater and tributaries is included in the model to estimate the influence on the water quality variation at downstream. The extents of contribution of the uncertainties influencing on the total uncertainty can be evaluated from the results of the model.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.