• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.200-210
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• 2006

This paper proposes the motion generation method in which the movement of the 3-links leg subsystem in constrained to slider-link and a singular posture can be easily avoided. This method is the realization of jumping control moving in a vertical direction, which mimics a cat's behavior. To consider the movement from the point of the constraint mechanical system, a robotics system for realizing the motion will change its configuration according to the position. The effectiveness of the proposed scheme is illustrated by simulation and experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.174-178
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• 1997

In this paper,we consider a LQG problem subject to the stochastic multirate system. By restating the problem as a periodic LQG problem, it is pointed out that the lack of measurements and control inputs in some time instants makes the problem singular. A method of transforming the problem into a nonsingular one enables us to obtain the solution,however which gives a resulting value of the LQG cost and the setimation error dynamic different with those of the original system. As a consequence, we present a optimal value of the original cost and the estimation error covariance of the original system,which are expressed by periodic Lyapunov equation respectively. The evaluation resulte can be exploited in comparing the control system performances and specifying the sampling rates.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.71-76
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• 2008

Nonlinear dynamic system under random excitation was analyzed by using stochastic method. A linearization method was used in order to linearize non-linear structural characteristics but the parametric excitation was used as it was given. An equivalent energy method which equalizes the expectation value of energy of the original nonlinear system and that of quasi-linearized system was proposed. Ito's differential rule was applied to obtain steady state moments. Quasi-linearization coefficients can be obtained the iterative calculation of linearization scheme and steady state moments. Monte Carlo simulation was used to verify the results of the proposed method. Nonlinear vibration of a slender beam was analyzed in this research. The analysis results were compared with Monte Carlo simulation result and showed good agreement. As the spectral density of the given excitation increased, the analysis results showed the better agreement with Monte Carlo simulation.

• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1007-1013
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• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• Wind and Structures
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• v.17 no.2
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• pp.203-225
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• 2013

An analysis framework for vehicle-bridge dynamic interaction system under turbulent wind is proposed based on the relevant theory of wind engineering and dynamics. Considering the fluctuating properties of wind field, the stochastic wind velocity time history is simulated by the Auto-Regressive method in terms of power spectral density function of wind field. The bridge is represented by three-dimensional finite element model and the vehicle by a multi-rigid-body system connected by springs and dashpots. The detailed calculation formulas of unsteady aerodynamic forces on bridge and vehicle are derived. In addition, the form selection of wind barriers, which are applied as the windbreak measures of newly-built railways in northwest China, is studied based on the suggested evaluation index, and the suitable values about height and porosity rate of wind barriers are studied. By taking a multi-span simply-supported box-girder bridge as a case study, the dynamic response of the bridge and the running safety indices of the train traveling on the bridge with and without wind barriers are calculated. The limit values of train speed with respect to different wind velocities are proposed according to the allowance values in the design code.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.420-427
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• 2006

In this study, wind loads transmitted to a transmission tower from transmission lines are mitigated using rotational viscoelastic dampers. First, the wind load characteristics in a transmission tower is investigated considering the effect of the transmission lines through stochastic analysis. The assemblage of the transmission line and insulator are modeled as a double pendulum system connected to the SDOF model of the tower. From the result of the stochastic analysis, the background component of the overturing moment caused by the wind loads acting on the transmission lines are found to have considerable portion in the total overturning moment. Based on this observation result, a strategy Installing rotational viscoelastic damper (VED) between tower arm and transmission line is proposed for the mitigation of the transmission line reactions, which play a role as dynamic loads on a transmission tower. For the purpose of verification, time history analysis is conducted for different wind velocities and VED parameters. The analysis result shows that the rotational VED is effective for the mitigation of the background component rather than the resonance component of the transmission line reactions and achieves the reduction ratio of 50% even for higher wind speed.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.128-137
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• 1992

An automatic noise detection system is developed to sense abnormal noises in operating a microwave electronic range. A noise detection method is presented which accounts for the effects of backgound and dynamic noises of the range. A recursive formula used as a noise estimator is a special case of the discrete-time Kalman filter in stochastic processes. Noise levels were measured using a noise acquisition processor in a closed room free of background noise, and detected signals were processes using a microcomputer. The results obtaines showed that the fault detection system should be fast in response to the data acquired and should be high in accuracy and reliability.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.349-354
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• 1999

The transfer function was introduced to establish the prediction method for the DO concentration at the intaking point of Kongju Water Works System. In the mose cases we analyze a single time series without explicitly using information contained in the related time series. In many forecasting situations, other events will systematically influence the series to be forecasted(the dependent variables), and therefore, there is need to go beyond a univariate forecasting model. Thus, we must bulid a forecasting model that incorporates more than one time series and introduces explicitly the dynamic characteristics of the system. Such a model is called a multiple time series model or transfer function model. The purpose of this study is to develop the stochastic stream water quality model for the intaking station of Kongju city waterworks in Keum river system. The performance of the multiplicative ARIMA model and the transfer function noise model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the transfer function noise model lead to the improved accuracy.