• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.13-17
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• 2002

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.21-21
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• 1999

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.867-868
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• 2011

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.405-419
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• 2022

Flood frequency analysis commonly used to design the hydraulic structures to minimize flood damage includes uncertainty. Therefore, the most appropriate design flood within a uncertainty should be selected in the final stage of a hydraulic structure, but related studies were rarely carried out. The total expected cost function introduced into the flood frequency analysis is a new approach for determining the optimal design flood. This procedure has been used as UNCODE (UNcertainty COmpliant DEsign), but the application has not yet been introduced in South Korea. This study introduced the mathematical procedure of UNCODE and calculated the optimal design flood using the annual maximum inflow of hydroelectric dams located in the Bukhan River system and results were compared with that of the existing flood frequency. The parameter uncertainty was considered in the total expected cost function using the Gumbel and the GEV distribution, and the Metropolis-Hastings algorithm was used to sample the parameters. In this study, cost function and damage function were assumed to be a first-order linear function. It was found that the medians of the optimal design flood for 4 Hydroelectric dams, 2 probability distributions, and 2 return periods were calculated to be somewhat larger than the design flood by the existing flood frequency analysis. In the future, it is needed to develop the practical approximated procedure to UNCODE.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.57-64
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• 2001

This paper propose a robust control method to achieve a desired system performance in spite of system uncertainty and disturbance uncertainty. The procedures of the robust controller based on QFT(Quantitative Feedback Theory) make template, bound and loop shaping which are considered by system parameter variations and performance specifications. To prove the efficiency, the designed controller is applied for an inverted pendulum which is so sensitive to the parameter variation and has a highly nonlinear and unstable characteristics. It is shown that the simulation and experimental results from the proposed controller are efficient in robustness of parameter variation and disturbance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.26-32
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• 2010

This paper proposes a new effective installed reserve rate in order to evaluate reliability of power system considering renewable generators, which include uncertainty of resource supply. It is called EIRR(effective installed reserve rate) in this paper. It is developed with considering capacity credit based on ELCC by using LOLE reliability criterion. While the conventional installed reserve rate index yields over-evaluation reliability of renewable generators, the proposed EIRR describes actual effective installed reserve rate. However, it is not the probabilistic reliability index as like as LOLE or EENS but another deterministic effective reliability index. The proposed EIRR is able to evaluate the realistic contribution to the reliability level for power system considering wind turbine generators and solar cell generators with high uncertainty in resource supply. The case study in model system as like as Jeju power system size presents a possibility that the proposed EIRR can be used practically as a new deterministic reliability index for generation expansion planning or operational planning in future.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 1997.11a
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• pp.117-122
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• 1997

This paper presents a study on the fuzzy based approach for the safety assessment of human body under ELF electric and magnetic(EM) field considering power system states. The analysis of ELF EM field based on quasi-static method is introduced. UP to the present, the analysis of ELF EM field has been conducted with the consideration of one transmission line, or a power line model only In this paper, however, the power system is included to model the expected and/or unexpected uncertainty caused by the load fluctuation and parameter changes and the states are classified into two types, normal state resulting from normal operation and emergency state from outages. In order to analyze the uncertainty in the normal state, the Monte Carlo Simulation, a statistic approach was introduced and line current and bus voltage distribution are calculated by a contingency analysis method, in the emergency state. To access the safety of human body, the approach based on fuzzy linguistic variable is adopted to overcome the shortcomings of the assessment by a crisp set concept. In order to validate the usefulness of the approach suggested herein, the case study using a sample system with 765(kV) was done. The results are presented and discussed.

• Journal of Power Electronics
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• v.10 no.5
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• pp.498-504
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• 2010

The output power fluctuations of renewable energy power plants such as wind turbine generators and photovoltaic systems result in frequency deviations and terminal voltage fluctuations. Furthermore, these power fluctuations also affect the turbine shaftings of diesel generators and gas-turbine generators which are the main power generation systems on isolated islands. Therefore, it is important to achieve torsional torque suppression. Since the measurement of torsional torque is technically difficult, and there is an uncertainty in the mechanical constants of the shaft torsional system. This paper presents an estimation system that estimates torsional torque by using a developed $H_{\infty}$ observer. In addition to the above functions, the proposed shaft torque observer incorporates a parameter identification system that aims to improve the estimation accuracy. The simulation results validate the effectiveness of the proposed $H_{\infty}$ observer and the parameter identification.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.93-100
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• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.