• 전자공학회논문지SC
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• 제41권2호
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• pp.45-52
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• 2004

본 논문에서는 슬라이딩 라인 함수의 각 요소를 간편 간접추론 퍼지 논리의 입력변수로 사용하여 슬라이딩 모드 제어기의 경계층을 모사하는 간편 간접추론 퍼지논리 경계층을 갖는 슬라이딩 모드 제어기를 설계하였다. 제안된 제어시스템은 별도의 비선형 함수를 구할 필요가 없으며, 네 개의 퍼지규칙으로 이루어지므로 간단하고 안정도 증명이 쉬운 장점을 가진다. 본 논문의 유효성을 비선형 시변 시스템에 적용하여 고찰하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.206-208
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• 1997

This paper presents a design of self_tuning fuzzy logic controller using Genetic Algorithms for power system stabilization. FPSS(Fuzzy Logic Power System Stabilized is applied to the KERI(Korea Electric Research Int.) power system simulator so that its efficiency can be investigated in real time control. Genetic Algorithms are used to determine fuzzy membership functions. Experiment results show the better performances with FPSS in comparison to no PSS.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1998년도 학술발표회논문집
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• pp.181-185
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• 1998

A speed controller of a induction motor using Microcontroller and Fuzzy logic is presented in the paper. Generally, fuzzy logic controller is known as a controller which can be coped with a non-linear and a complex system. A fuzzy logic is used for robust and fast speed control and space vector modulation method is used for PWM wave generation in this proposed system. The results of experiment show excellence of the proposed system and that the proposed system is appropriate to control the speed of a induction motor for industrial application.

• Journal of Electrical Engineering and Technology
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• 제5권1호
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• pp.129-139
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• 2010

To be satisfied with complex load condition of electric vehicle, fuzzy logic control (FLC) is applied to improve speed response and system robust performance of induction traction machine based on indirect rotor field orientation control. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels of lightweight electric vehicle by means the vehicle used for passenger transportation. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling, independently, every driving wheel to turn at different speeds in any curve. Our electric vehicle fuzzy inference system control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency and the robustness of the proposed control with good performances compared with the traditional PI speed control, the FLC induction traction machine presents not only good steady characteristic, but with no overshoot too.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 동계학술발표대회 논문집
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• pp.393-398
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• 2008

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of the unique property of a $CO_2$ as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the efficient operation. The high-side pressure algorithm being composed of the pressure setpoint algorithm and the pressure setpoint reset algorithm was developed. The pressure setpoint algorithm, by using a least square method, was developed. The pressure setpoint reset algorithm, by using a fuzzy logic and by using a proportional logic, was also developed and compared. Simulation results showed that a proportional logic was more practical than a fuzzy logic for the pressure setpoint reset algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.352-357
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• 1987

The Auto Tuning Controller is designed using Fuzzy set theory. And to verify its validity it is Applied to the Auto Tuner of hydraulic Control System. Fuzzy Tuning Procedures are written by linguistic model and translated into C language formation by preprocessor. Then it is executed with state feedback controller in real time, Fuzzy Logic Controller adjusts state feedback gain by proper tuning logic in each step to satisfy the desired maximum overshoot and settling time.

• 수산해양기술연구
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• 제30권3호
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• pp.189-198
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• 1994

This paper describes the model of a simplified trawl system and a control method by using fuzzy algorithm in controlling the depth of trawl gear. Fuzzy logic control rules are sets of linguistic expression that are used by an experienced performer in real operation. For real time processing of the control rules, the look-up tables are used. Computer simulation results indicate that the proposed fuzzy controller shows fast response with minimum steady-state error and robustness properties to the simulated disturbance.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.99-102
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• 2001

It has well known that the congestion of traffic and it's distribution. There are very important problems in the traffic control systems. In this paper, we will purpose an ITFS(Intelligent Traffic Forecasting System) which can determine the car classes and transport them to ITS(Intelligent Traffic control System). The system will be used the Inductive Loop Detector(ILD)and the Fuzzy logic and shown the effectiveness by the computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.140-142
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• 2001

Three single loop fuzzy logic controllers are designed independently for the control of boiler system of fossil-power plant. The control rules and the membership functions of proposed fuzzy logic control system are generated automatically without using plant model. The simulation shows successful results for wide range operation of boiler system of fossil-power plant.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.352-362
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• 2014

In this paper, a fuzzy logic controller is designed for a DC motor which can be used for navigation control of mobile robots. These mobile robots can be used for agricultural, defense and assorted social applications. The robots used in these fields can reduce manpower, save human life and can be operated using remote control from a distant place. The developed fuzzy logic controller is used to control navigation speed and steering angle according to the desired reference position. Differential drive is used to control the steering angle and the speed of the robot. Two DC motors are connected with the rear wheels of the robot. They are controlled by a fuzzy logic controller to offer accurate steering angle and the driving speed of the robot. Its location is monitored using GPS (Global Positioning System) on a real time basis. IR sensors in the robot detect obstacles around the robot. The designed fuzzy logic controller has been implemented in a robot, which depicts that the robot could avoid obstacle as well as perform its operation efficiently with remote online control.