• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.

• Korean Journal of Applied Biomechanics
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• v.33 no.1
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• pp.34-44
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• 2023

Objective: The purpose of this study was to examine the effects of increasing running speed on human stability by comparing the Lyapunov Exponent (LyE) and Coefficient of Variation (CV) methods, with the goal of identifying key variables and uncovering new insights. Method: Fourteen adult males (age: 24.7 ± 6.4 yrs, height: 176.9 ± 4.6 cm, weight: 74.7 ± 10.9 kg) participated in this study. Results: In the CV method, significant differences were observed in ankle (flexion-inversion/eversion; p < .05) and hip joint (internal-external rotation; p < .05) movements, while the center of mass (COM) variable in the coronal axis movements showed a significant difference at the p < .001 level. In the LyE method, statistical differences were observed at the p < .05 level in knee (flexion-extension), hip joint (internal-external rotation) movements, and COM across all three directions (sagittal, coronal, and transverse axis). Conclusion: Our results revealed that the stability of the human body is affected at faster running speeds. The movement of the COM and ankle joint were identified as the most critical factors influencing stability. This suggests that LyE, a nonlinear time series analysis, should be actively introduced to better understand human stabilization strategies.

• Knowledge Management Research
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• v.22 no.4
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.