• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.410-417
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• 2009

The objective of this paper is to study the discharge phenomenon for a point-plane air interval using an original fuzzy logic system. Firstly, a physical model based on streamer theory with consideration of the space charge fields due to electrons and positive ions is proposed. To test this model we have calculated the breakdown threshold voltage for a point-plane air interval. The same model is used to determine the discharge steps for different configurations as an inference data base. Secondly, using results obtained by the numerical simulation of the previous model, we have introduced the fuzzy logic technique to predict the breakdown threshold voltage of the same configurations used in the numerical model and make estimation on the insulating state of the air interval. From the comparison of obtained results, we can conclude that they are in accordance with the experimental ones obtained for breakdown discharges in different point-plane air gaps collected from the literature. The proposed study using fuzzy logic technique shows a good performance in the analysis of different discharge steps of the air interval.

• 한국자동차공학회논문집
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• 제6권5호
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• pp.138-145
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• 1998

Recently, TCS(Traction Control System) is attracting attention, because it maintains traction ability and steerability of vehicles on low-$\mu$ surface roads by controlling the slip rate between tire and road surface. The development of TCS control law is difficult due to the highly nonlinearity and uncertainty involved in TCS. A fuzzy logic approach is appealing for TCS. In this paper, fuzzy logic controller for TCS is introduced and evaluated by the computer simulation with 8 DOF vehicle model. The result indicate that the fuzzy logic TCS improves vehicle's stability and steerability.

• Computers and Concrete
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• 제14권3호
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• pp.233-245
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• 2014

In this paper, a rule based Mamdani type fuzzy logic model for prediction of slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes were discussed. In the model steel rebar diameters and development lengths were used as inputs. The FL model and experimental results, the coefficient of determination R2, the Root Mean Square Error were used as evaluation criteria for comparison. It was concluded that FL was practical method for predicting slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes.

• 한국인터넷방송통신학회논문지
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• 제23권5호
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• pp.71-76
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• 2023

본 논문에서는 딥러닝을 이용한 영상 분할에서 성능을 향상하기 위해 퍼지 논리를 적용하는 퍼지 딥러닝 모델인 퍼지 U-Net을 제안한다. 퍼지 논리를 이용한 퍼지 모듈을 영상 분할에서 우수한 성능을 보이는 딥러닝 모델인 U-Net에 결합하여 다양한 형태의 퍼지 모듈을 시뮬레이션하였다. 제안된 딥러닝 모델의 퍼지 모듈은 이미지의 특징맵과 해당 분할 결과 사이의 본질적이고 복잡한 규칙을 학습다. 이를 위해 치아 CBCT 데이터에 적용하여 제안된 방법의 우수성을 입증하였다. 시뮬레이션 결과 제안된 퍼지 U-Net에서 더하기 스킵 연결을 사용한 모델의 ADD-RELU 퍼지 모듈 구조의 성능이 시험용 데이터에 대해 0.7928로 가장 우수한 것을 볼 수 있다.

• 한국컴퓨터정보학회논문지
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• 제12권5호
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• pp.49-56
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• 2007

계산 그리드 컴퓨팅은 수많은 컴퓨팅 자원들을 이용하여, 슈퍼 컴퓨팅이나 이전의 분산 컴퓨팅으로 해결 할 수 없는 대용량의 연산 문제를 해결한다. 계산 그리드 컴퓨팅 환경에서의 자원은 이 기종으로 구성되어, 효율적인 작업 처리를 위해서는 스케줄링 기법이 필요하다. 본 논문에서는 계산 그리드에서 효율적인 작업 스케줄링을 위하여 퍼지로직 기반의 그리드 작업 스케줄링 모델을 제안한다. 퍼지로직 기반의 그리드 작업 스케줄링 모델은 퍼지로직을 이용하여 자원의 효율성을 평가하며, 평가된 기반으로 그룹을 구성하여 작업을 할당하는 모델이다. 우리는 DEVS 모델링 & 시뮬레이션 환경에서 시뮬레이션 모델을 구성하고 Random 스케줄링과 MCT 스케줄링 모델과의 비교 실험을 통하여 제안된 퍼지로직 기반의 그리드 작업 스케줄링 모델이 작업완료시간, 작업손실, 통신량을 개선함으로써 더욱 더 안정적이고 빠른 작업 처리 서비스를 그리드 사용자에게 제공할 수 있다는 사실을 증명하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권3호
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• pp.361-365
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• 2004

In this paper, we present the modeling of time series data which are corrupted by noise via nonsingleton fuzzy logic system. Nonsingleton fuzzy logic system (NFLS) is useful in cases where the available data are corrupted by noise. NFLS is a fuzzy system whose inputs are modeled as fuzzy number. The abilities of NFLS to approximate arbitrary functions, and to effectively deal with noise and uncertainty, are used to analyze corrupted time series data. In the simulation results, we compare the results of the NFLS approach with the results of using only a traditional fuzzy logic system.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권1호
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• pp.48-55
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm adjusts the driving torque for restraining re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy, These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.30-32
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy.

• Advances in Computational Design
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• 제4권4호
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• pp.367-379
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• 2019

Multiple Inputs and Multiple Outputs (MIMO) Fuzzy logic model is developed to predict the engine performance and emission characteristics of pongamia pinnata biodiesel with hydrogen injection. Engine performance and emission characteristics such as brake thermal efficiency (BTE), brake specific energy consumption (BSEC), hydrocarbon (HC), carbon monoxide (CO), carbon dioxide ($CO_2$) and nitrous oxides ($NO_X$) were considered. Experimental investigations were carried out by using four stroke single cylinder constant speed compression ignition engine with the rated power of 5.2 kW at variable load conditions. The performance and emission characteristics are measured using an Exhaust gas analyzer, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends (Diesel, B10, B20 and B30) and engine load conditions. Fuzzy logic model uses triangular and trapezoidal membership function because of its higher predictive accuracy to predict the engine performance and emission characteristics. Computational results clearly demonstrate that, the proposed fuzzy model has produced fewer deviations and has exhibited higher predictive accuracy with acceptable determination correlation coefficients of 0.99136 to 1 with experimental values. The developed fuzzy logic model has produced good correlation between the fuzzy predicted and experimental values. So it is found to be useful for predicting the engine performance and emission characteristics with limited number of available data.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권2호
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• pp.107-113
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• 2004

This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.