• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.2-2
• /
• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.264-264
• /
• 2000

In this paper, we propose a method to automatically extract stable visual landmarks from observed data for a mobile robot with stereo vision system. The robot selects as stable landmarks vertical line segments which are distinct and on planar surfaces, because they are expected to be observed reliably from various view-points. When the robot moves, it uses several, less uncertain landmarks for estimating its motion. Experimental results in real scenes show the validity of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.3 no.1
• /
• pp.29-40
• /
• 1993

The role of principles of minimum uncertainty in dealing with the reconstruction problem of systems with dynamic properties is discussed. The aim of the reconstruction problem, one of two problems addressed by reconstruct ability analysis, is to determine the smallest possible sub-systems by which a given overall system can be adequately represented.

• Proceedings of the KIEE Conference
• /
• 2003.07c
• /
• pp.1744-1746
• /
• 2003

This paper represents the development of national standard (NS) for lightning impulse (LI) voltage measuring system rated 400 kV. A traceability of the NS to the international standard could be achieved by the intercomparison test with Helsinki University. According to the IEC 60060-2, a measurement uncertainty was assessed. As a result of the tests, a measurement uncertainty and step response characteristics were satisfied with the requisite for NS.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.4
• /
• pp.307-316
• /
• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.27 no.6
• /
• pp.605-613
• /
• 2014

Epistemic uncertainty, the lack of knowledge, is often more important than aleatory uncertainty, variability, in estimating reliability of a system. While the probability theory is widely used for modeling aleatory uncertainty, there is no dominant approach to model epistemic uncertainty. Different approaches have been developed to handle epistemic uncertainties using various theories, such as probability theory, fuzzy sets, evidence theory and possibility theory. However, since these methods are developed from different statistics theories, it is difficult to interpret the result from one method to the other. The goal of this paper is to compare different methods in handling epistemic uncertainty in the view point of calculating the probability of failure. In particular, four different methods are compared; the probability method, the combined distribution method, interval analysis method, and the evidence theory. Characteristics of individual methods are compared in the view point of reliability analysis.

• Journal of Korea Port Economic Association
• /
• v.36 no.4
• /
• pp.93-106
• /
• 2020

Trade is an important economic activity. In particular, since the establishment of the World Trade Organization (WTO), the scope of trade has been expanding due to events such as the entry of China into the WTO in 2001, the establishment of a multilateral trading system, mitigation and integration of trade barriers, and the establishment of the free trade agreement (FTA). Despite the expansion of the trade market, however, extreme events such as the 2008 global financial crisis, the 2016 Brexit, and the 2018 US-China trade war have had a direct negative impact on the trade market. Therefore, the present this study analyzed the dependence structure between the international shipping freight rate index, a variable representing trade activities, and the trade uncertainty between the US and China. The following is a summary of the analysis results. First, the US-Chinese trade policy uncertainty and international shipping freight rate index presented a Frank copula and rotated Clayton copula 270° distribution, respectively, showing the same distribution structure for each country. Second, the Kendall's tau correlation revealed a negative dependence between the international shipping freight rate index and US-Chinese trade policy uncertainty. The degree of dependence was greater in the combination of uncertainty in China's trade policy and international shipping freight rates. In other words, the dependence of global demand and trade policy uncertainty confirmed that China was stronger than the US. Finally, the tail dependence results revealed that the US-Chinese trade policy uncertainty and international shipping freight rates were independent of each other. This means that extreme events related to the trade policy uncertainty or international shipping rate index were not affected by each other.

• Journal of Korea Water Resources Association
• /
• v.56 no.8
• /
• pp.509-520
• /
• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.10
• /
• pp.1318-1326
• /
• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.

• Structural Engineering and Mechanics
• /
• v.63 no.1
• /
• pp.47-53
• /
• 2017

The fundamental goal of this study is to minimize the uncertainty of the median fragility curve and to assess the structural vulnerability under earthquake excitation. Bayesian Inference with Markov Chain Monte Carlo (MCMC) simulation has been presented for efficient collapse response assessment of the independent intake water tower. The intake tower is significantly used as a diversion type of the hydropower station for maintaining power plant, reservoir and spillway tunnel. Therefore, the seismic fragility assessment of the intake tower is a pivotal component for estimating total system risk of the reservoir. In this investigation, an asymmetrical independent slender reinforced concrete structure is considered. The Bayesian Inference method provides the flexibility to integrate the prior information of collapse response data with the numerical analysis results. The preliminary information of risk data can be obtained from various sources like experiments, existing studies, and simplified linear dynamic analysis or nonlinear static analysis. The conventional lognormal model is used for plotting the fragility curve using the data from time history simulation and nonlinear static pushover analysis respectively. The Bayesian Inference approach is applied for integrating the data from both analyses with the help of MCMC simulation. The method achieves meaningful improvement of uncertainty associated with the fragility curve, and provides significant statistical and computational efficiency.