• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.245-253
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• 2017

The relative displacement of a piping system installed between isolated and nonisolated structures in a severe earthquake might be larger when without a seismic isolation system. As a result of the relative displacement, the seismic risks of some components in the building could increase. The possibility of an increase in seismic risks is especially high in the crossover piping system in the buildings. Previous studies found that an elbow which could be ruptured by low-cycle ratcheting fatigue is one of the weakest elements. Fatigue curves for elbows were suggested based on component tests. However, it is hard to find a quantitative evaluation of the ultimate state of piping elbows. Generally, the energy dissipation of a solid structure can be calculated from the relation between displacement and force. Therefore, in this study, the ultimate state of the pipe elbow, normally considered as failure of the pipe elbow, is defined as leakage under in-plane cyclic loading tests, and a failure estimation method is proposed using a damage index based on energy dissipation.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.237-242
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• 2022

Acquiring high-quality images in control and measurement systems is one of the important factors. Among image acquisition technologies, SFF (Shape from Focus) is a technology for recovering a 3D shape by acquiring 2D images with different focus levels by moving an object at a predetermined step size along the optical axis. For SFF, when an object is moved at a constant step size, mechanical vibration, referred as jitter noise, occurs in each step along the optical axis. In this paper, a new state estimation filter is designed and applied for reducing the jitter noise. For the application of the proposed method, the jitter noise and focus curves are modeled as Gaussian function. Experimental results demonstrate the effectiveness of proposed method.

• Journal of the Korean Operations Research and Management Science Society
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• v.6 no.2
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• pp.57-64
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• 1981

This paper develops a method of modifying the usual maximum likelihood estimators of the parameters of a two state Markov process when the trajectory of the process can only he observed at regular epochs. The method utilizes the limiting behaviors of the process and the properties of state transition counts. An efficient adaptive strategy to be used together with the modified estimator is also proposed. The properties of the new estimators and the adaptive strategy are investigated using Monte Carlo simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.2
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• pp.122-129
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• 1988

A design method of decentralized state observer for large scale interconnected systems is proposed by the use of interconnection rejection approach and interconnection modelling technique. The proposed design method is developed based on the interconnection partitioning. Therefore partitioning conditions are suggested. And the conditions for observer pole assignment and observer parameter determination procedures are described for possible interconnection patterns. The decentralized state observer gives good estimates without any information on the interconnection variables and estimations. In addition, a numerical example is given to explain the design procedures and to show the estimation performance of the decentralized observer.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.792-799
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• 2008

Motion estimation is crucial in a remote control for its convenience or accuracy. Time delays, however, can occur in the problem because data communication is required through a network. In this paper, state estimation problem with uncertain time delayed measurements is addressed. In dynamic system with noise, after taking measurements, it often requires some time until that is available in the filter algorithm. Standard filters not considering this time delays cannot be used since the current measurement is related with a past state. These delayed measurements are solved with augmented extended Kalman filter, and the uncertainty of delayed time is also resolved based on an explicit formulation. The proposed method is analyzed and verified by simulations.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.506-509
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• 2006

Extended Kalman Filter iterate the prediction and the filtering based on Initial state for the next time step. EKF method for the estimation of nonlinear parameters of a structural dynamic system is necessary that initial of state vector and error covariance matrix. Because those are unknown exactly, generally selected random values. That occasion observability problem appear because of unknown initial values. In this study, for the estimation of the nonlinear parameters, a simple one degree of Freedom example is carried out by Extended Kalman Filter. And initial value assumption for Parameter Estimation of Dynamic System are developed. The result of analysis is compared with calculated standard values.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1249-1254
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• 2006

Existing adaptive observers may cause the parameter drifts due to disturbances even if state estimation errors remain small. To avoid the drift phenomena in the presence of bounded disturbances, several robust adaptive observers have been introduced addressing bounds in state and parameter estimates. However, it is not easy for these observers to manipulate the size of the bounds with the selection of the observer gain. In order to reduce estimation errors, this paper introduces the (equation omitted) gain minimization problem in the adaptive observer structure, which minimizes the (equation omitted) gain between disturbances and estimation errors. The stability condition of the adaptive observer is reformulated as a linear matrix inequality, and the observer gain is optimally chosen by solving the convex optimization problem. The estimation performance is demonstrated through a numerical example.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.447-448
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• 2013

This paper investigates a new approach based on the fuzzy-logic controlled methodology that is suitable for analyzing and evaluating large format $LiMn_2O_4$ cell performance via online state-of-health (SOH) estimation for energy storage system (ESS) applications. First of all, the values of the cell resistance R and maximum cell capacity $Q_{max}$ are calculated from three factors such as voltage, current, and time that were measured by discharging/charging sequence. Then, using two values R and $Q_{max}$ previously calculated, present SOH of an arbitrary $LiMn_2O_4$ cell can be estimated using the defined fuzzy-logic inference system. The main advantage of this approach is wide parameters tuning possibility for good correspondence of SOH decay with other accurate estimation method and the possibility to perform suitable online SOH estimation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.545-550
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.