• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1230-1242
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• 2007

This paper describes an IIR/FIR fusion filter for a nonlinear system, and analyzes the stability of the fusion filter. The fusion filter is applied to INS/GPS integrated system, and the performance is verified by simulation and experiment. In the fusion filter, an IIR-type filter (SPKF) and FIR-type filter (MRHKF filter) are processed independently, then the two filters are merged using the mixing probability calculated using the residuals and residual covariance information of the two filters. The merits of the SPKF and the MRHKF filter are embossed and the demerits of the filters are diminished via the filter fusion. Consequently, the proposed fusion filter has robustness against to model uncertainty, temporary disturbing noise, large initial estimation error, etc. The stability of the fusion filter is verified by showing the closeness of the states of the two sub filters in the mixing/redistribution process and the upper bound of the error covariance matrices. This fusion filter is applied into INS/GPS integrated system, and important factors for filter processing are presented. The performance of the INS/GPS integrated system designed using the fusion filter is verified by simulation under various error environments and is confirmed by experiment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.1
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• pp.33-40
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• 2009

In the present experimental study, the pumping performances of diffuser/nozzle based piezoelectric micropumps are estimated with different operating factors and geometries. Here, the effects of the input voltage and frequency on the pumping performances have been examined together with the influences of the positions of the inlet and outlet. The results show that the flow rate of the micropump is larger with larger input voltage with the largest flow rates for the frequency to be close to 6.0 Hz all through the current experimental study. Also, it has been found that the positions of the inlet and outlet affect much on the performance of the piezoelectric micropumps. Error estimation has been carried out for the evaluation of the pumping performance in association with the uncertainty of the measurement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.3
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• pp.295-302
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• 1998

In this paper, a new auto-tuning PI controller for the speed servo system of a PMSM is designed by using limited step response characteristics. The method is proposed that gets information about auto-tuning of PI regulator by the injection of step input, called limited input, during a transient response time of control. System parameter estimation and speed control could be continuously executed. This means that in despite of system uncertainty the system information obtained by limited input can be continuously applied to the PI regulator. We demonstrate the effectiveness of the proposed auto-tuning algorithm through simulation and experiment result of the speed control for a PMSM having monotone increasing step response.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• Journal of Navigation and Port Research
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• v.31 no.9
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• pp.763-769
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• 2007

A narrow loop noise bandwidth method is desirable to reduce the error of raw measurements due to the thermal noise. However, it degrades the performance of GPS initial synchronization such as mean acquisition time. And it restricts the loop noise bandwidth to a fixed value determined by the lower bound of the allowable range of carrier-to-noise power ratio, so that it is difficult to optimally track GPS signal. In order to make up for the weak points of the fixed-type narrow loop noise bandwidth method and simultaneously minimize the error of code and carrier measurements, this paper proposes a stepwise-type adaptive bandwidth algorithm for DGPS reference receivers. In this paper, it is shown that the proposed adaptive bandwidth algorithm can provide more accurate measurements than those of the fixed-type narrow loop noise bandwidth method, in view of analyzing the simulation results between two signal tracking algorithms. This paper also carries out sensitivity analysis of the proposed adaptive bandwidth algorithm due to the estimation uncertainty of carrier-to-noise power ratio. Finally the analysis results are verified by the experiment using GPS simulator.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1501-1510
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• 2014

Low voltage direct current (LVDC) distribution system is a suitable techno-economic candidate which can create an innovative solution for distribution network development with respect to rural electrification. This research focuses on the use of LVDC distribution system to replace some of KEPCO's existing traditional medium voltage alternating current (MVAC) distribution network for rural electrification in South Korea. Considering the technical and economic risks and benefits involved in such project, a comparative techno-economic analysis on the LVDC and the MVAC distribution networks is conducted using economic assessment method such as the net present value (NPV) on a discounted cash flow (DCF) basis as well as the sensitivity analysis technique. Each would play a role in an economic performance indicator and a measure of uncertainty and risk involved in the project. In this work, a simulation model and a computational tool are concurrently developed and employed to aid the techno-economic analysis, evaluation, and estimation of the various systems efficiency and/or performance.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.869-877
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• 2016

Necessity has compelled man to improve upon the art of tapping wind energy for power generation; an apt reliever of strain exerted on the non-renewable fossil fuel. The power generation in a Wind Farm (WF) depends on site and wind velocity which varies with time and season which in turn determine wind power modeling. It implies, the development of an accurate wind speed model to predict wind power fluctuations at a particular site is significant. In this paper, Box-Jenkins ARIMA (Auto Regressive Integrated Moving Average) time series model for wind speed is developed for a 99MW wind farm in the southern region of India. Because of the uncertainty in wind power developed, the economic viability and reliability of power generation is significant. Life Cycle Costing (LCC) method is used to determine the economic viability of WF generated power. Reliability models of WF are developed with the help of load curve of the utility grid and Capacity Outage Probability Table (COPT). ARIMA wind speed model is used for developing COPT. The values of annual reliability indices and variations of risk index of the WF with system peak load are calculated. Such reliability models of large WF can be used in generation system planning.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1412-1422
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• 2016

Austenitic stainless steels (ASSs) are widely used for nuclear pipes as they exhibit a good combination of mechanical properties and corrosion resistance. However, high tensile residual stresses may occur in ASS welds because postweld heat treatment is not generally conducted in order to avoid sensitization, which causes a stress corrosion crack. In this study, round robin analyses on stress intensity factors (SIFs) were carried out to examine the appropriateness of structural integrity assessment methods for ASS pipe welds with two types of circumferential cracks. Typical stress profiles were generated from finite element analyses by considering residual stresses and normal operating conditions. Then, SIFs of cracked ASS pipes were determined by analytical equations represented in fitness-for-service assessment codes as well as reference finite element analyses. The discrepancies of estimated SIFs among round robin participants were confirmed due to different assessment procedures and relevant considerations, as well as the mistakes of participants. The effects of uncertainty factors on SIFs were deducted from sensitivity analyses and, based on the similarity and conservatism compared with detailed finite element analysis results, the R6 code, taking into account the applied internal pressure and combination of stress components, was recommended as the optimum procedure for SIF estimation.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.366-366
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• 2012

확률강우량은 하천설계, 수자원설계 및 계획을 위한 기초자료로 활용되며 최근 이상기후 및 기후변화로 인한 극치강우의 빈도 및 양적 증가로 인한 확률강우량 산정의 불확실성 분석에 대한 관심이 크게 증가하고 있다. 수문빈도 해석에 있어서 대부분 지역이 50년 이하의 수문자료가 이용되고 있으며 수문설계에서 요구되는 50년 이상의 확률강수량 추정시에는 상당한 불확실성을 내포하고 있다. 이러한 점에서 본 연구에서는 자료연수에 따른 Sampling Error와 분포형의 매개변수의 불확실성을 고려한 해석모형을 구축하고자 한다. 빈도해석에서 매개변수를 추정하기 위해서는 일반적으로 모멘트법, 최우도법, 확률가중모멘트법이 이용되고 있으나 사용되는 분포형에 따라서 통계학적으로 불확실성 구간을 정량화하는 과정이 난해할 뿐만 아니라 극치 수문자료가 Thick-Tailed분포의 특성을 가짐에도 불구하고 신뢰구간 산정시 정규분포로 가정하는 등 기존 해석 방법에는 많은 문제점을 내포하고 있다. 본 연구에서는 이러한 매개변수의 불확실성 평가에 있어서 우수한 해석능력을 발휘하는 Bayesian기법을 도입하여 분포형의 매개변수를 추정하고 매개변수 추정과 관련된 불확실성을 평가하고자 한다. 이와 별개로 자료연한에 따른 Sampling Error를 추정하기 위해서 Bootstrapping 기반의 해석모형을 구축하고자 하며 최종적으로 빈도해석시에 나타나는 불확실성을 종합적으로 검토하였다. 빈도해석을 위한 확률분포형으로 GEV(generalized extreme value)분포를 이용하였으며 Gibbs 샘플러를 활용한 Bayesian Markov Chain Monte Carlo 모의를 기본 해석모형으로 활용하였다.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.