• 한국군사과학기술학회지
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• 제3권2호
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• pp.71-80
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• 2000

In Underwater Flight Vehicle depth control system, the followings must be required. Firstly, It need robust depth control performance which can get over parameter variation, modeling error and disturbance. Secondly, It need no oveshoot phenomenon to avoid colliding with ground surface and obstables. Thirdly, It need continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, It need effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose the Fuzzy-PID depth controller with the control parameter interpolators. Simulation results show the proposed control scheme has robust and accurate performance with continuous control input.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 95 KFIS Workshop Realization of Human Friendly System Based on Soft Computiong Techniques
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• pp.124-140
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• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• 전기학회논문지
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• 제67권1호
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• pp.96-102
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• 2018

For efficient operating strategy of electric power system, forecasting of daily peak electric load is an important but difficult problem. Therefore a daily peak electric load forecasting system using a neural network and fuzzy system is presented in this paper. First, original peak load data is interpolated in order to overcome the shortage of data for effective prediction. Next, the prediction of peak load using these interpolated data as input is performed in parallel by a neural network predictor and a fuzzy predictor. The neural network predictor shows better performance at drastic change of peak load, while the fuzzy predictor yields better prediction results in gradual changes. Finally, the superior one of two predictors is selected by the rules based on rough sets at every prediction time. To verify the effectiveness of the proposed method, the computer simulation is performed on peak load data in 2015 provided by KPX.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권1호
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• pp.31-38
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• 2013

Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.

• Wind and Structures
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• 제38권3호
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• pp.161-170
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• 2024

In recent years, there have been an increasing number of experimental studies showing the need to include robustness criteria in the design process to develop complex active control designs for practical implementation. The paper investigates the crosswind aerodynamic parameters after the blocking phase of a two-dimensional square cross-section structure by measuring the response in wind tunnel tests under light wind flow conditions. To improve the accuracy of the results, the interpolation of the experimental curves in the time domain and the analytical responses were numerically optimized to finalize the results. Due to this combined effect, the three aerodynamic parameters decrease with increasing wind speed and asymptotically affect the upper branch constants. This means that the aerodynamic parameters along the density distribution are minimal. Taylor series are utilized to describe the fuzzy nonlinear plant and derive the stability analysis using polynomial function for analyzing the aerodynamic parameters and numerical simulations. Due to it will yield intricate terms to ensure stability criterion, therefore we aim to avoid kinds issues by proposing a polynomial homogeneous framework and utilizing Euler's functions for homogeneous systems. Finally, we solve the problem of stabilization under the consideration by SOS (sum of squares) and assign its fuzzy controller based on the feasibility of demonstration of a nonlinear system as an example.

• 한국습지학회지
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• 제7권4호
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• pp.97-107
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• 2005

분포형 모형이 개발되어 지면서 이러한 유역의 공간적인 특성을 고려한 정확한 강우 자료와 조밀한 계측망의 요구는 더욱 커지고 있다. 그러나 현실적으로 조밀한 계측망에 의해 측정된 정확한 강우 자료를 얻기는 쉽지 않다. 일반적으로 강우관측소가 적정 밀도를 가지고 유역을 대표 하도록 설치되어 있으나 부족한 실정이고, 설치되어 있더라도 강우의 시 공간적 변동성을 반영하기가 쉽지 않다. 또한 여러 가지 이유로 결측이 되는 경우도 있다. 강우는 측정된 점 관측 자료를 이용해 유역의 평균 강우분포를 추정하게 된다. 따라서 결측 강우자료는 시간의 연속성 측면에서 그 보정이 반드시 필요하며 보정 후 강우자료의 공간적 분포를 산정할 수 있을 것이다. 본 연구에서는 결측 강우량의 보정을 위하여 퍼지-유전자 알고리즘을 이용하였는데 이 방법을 기존의 방법 즉, 산술평균법, 역거리법, 년정상강우량법, 거리-고도비율법과 비교하였다. 보정결과 기존의 방법은 실측의 70~80%의 정확도를 보였으나 퍼지-유전자 알고리즘은 90%정도의 정확도를 보였다. 특히, 민감도 분석 결과를 바탕으로 수평거리와 고도차에 대한 적정 차수를 제안하였다.

• 한국군사과학기술학회지
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• 제4권2호
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• pp.30-41
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, It needs a robust performance which can get over the nonlinear characteristics due to hull shape. Second, It needs an accurate performance which has the small overshoot phenomenon and steady state error to avoid colliding with ground surface and obstacles. Third, It needs a continuous control input to reduce the acoustic noise. Finally, It needs an effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose a Intelligence depth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed control scheme has robust and accurate performance by continuous control input and has no speed dependency problem.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.176.2-176
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over nonlinear characteristics. Second, it needs accurate performance which have small overshoot phenomenon and steady state error. Third, it needs continuous control input. Finally, it needs interpolation method which can solve the speed dependency problem of controller parameters. To solve these problems, we propose adepth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• 통합자연과학논문집
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• 제12권1호
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• pp.14-19
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• 2019

In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.

• 한국콘텐츠학회논문지
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• 제9권5호
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• pp.84-90
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• 2009

본 논문에서는 최근 여러 분야에서 불확실성에 대한 예측을 위해 사용되는 Fuzzy 추론법을 OFDM(Othgonal Frequency Division Multiplexing)의 채널추정 방식에 적용함으로써 향상된 성능과 낮은 복잡도를 갖는 새로운 채널추정 방식을 제안하였다. 제안된 방식은 LS(Least Square) 채널추정 이전에 Pilot을 이용하여 Fuzzy추론법에 의하여 채널의 통계적 특성을 계산하고 이에 대한 보간을 해 줌으로써 채널추정 성능을 향상시키는 방식이다. QPSK(Quadrature Phase Shift Keying)를 적용한 시뮬레이션 결과 제안된 채널추정 방식은 MSE(Mean Square Error)가 $10^{-3}$인 지점에서 MMSE(Mimimum Mean Square Error) 채널추정 방식보다는 약 1.3 dB 정도 성능이 열화되는 것으로 나타났지만 LS 채널 추정 방식과 비교하면 약 5.5 dB 정도의 성능 이득이 있는 것으로 분석되었으며, SER(Symbol Error Rate)은 SNR(Signal to Noise Ratio)이 20 dB인 지점에서 MMSE 채널추정 방식과 제안된 채널추정방식이 각각 $10^{-1.96}$, $10^{-1.93}$ 정도로 유사한 성능을 보이는 것으로 분석되었고, LS 채널추정 방식 보다 약 $10^{-0.35}$ 정도 제안된 방식의 성능이 향상된 것으로 분석되었다.