• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1235-1244
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• 2017

This paper proposes a fuzzy logic controlled new topology of high voltage gain zero voltage switching (ZVS) asymmetrical PWM full-bridge DC-DC boost converter for constant load and high power applications. The APWM full-bridge stage provides high voltage gain and soft-switching characteristics increase the efficiency and reduce the switching losses. Fuzzy logic controller (FLC) improves the performance and dynamic characteristics of the proposed converter. A comparison with a classical proportional-integral (PI) controller demonstrates the high performances of the proposed technique in terms of effective output voltage regulation under different operating conditions. Simulation is done by integrating two different simulation platforms $PSIM^{(R)}$ and $Matlab^{(R)}/Simulink^{(R)}$ by using SimCoupler tool of $PSIM^{(R)}$. Experimental results using 120W load have been provided to validate the results.

• Journal of Biosystems Engineering
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• 제22권4호
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• pp.487-496
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• 1997

A fuzzy logic controller(FLC) was developed for the autonomous travel of speedsprayer in an orchard. The autonomous travel with the FLC was graphically simulated under the conditions of an ordinary standard orchard. Differential global positioning system(DGPS) was used to find the direction of running and four ultrasonic sensors were used to detect obstacles during the running. The simulation results showed that the speedsprayer, by the FLC combined with DGPS and the ultrasonic sensors. could overcome the turning problem at comers which could not be solved with such a system as machine vision and might be operated autonomously.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1034-1036
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• 1996

In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

• 공학교육연구
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• 제3권1호
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• pp.21-26
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• 2000

월드 와이드 웹은 사이버 교육에 있어서 인터넷을 통한 새로운 기회를 제공한다. 웹은 다른 네트워크 기술과 결합하여 학습자에게 유용한 교육정보를 제공하는데 유용하다. 따라서, 본 논문의 목적은 인터넷상에서 퍼지 논리 제어기의 개념을 이해하기 위한 자바 애플릿을 개발하는 것이다. 개발된 자바 애플릿은 4개의 프레임(퍼지화기, 제어규칙, 추론 엔진, 비퍼지화기)으로 구성이 되어 있다. 데이터의 전송은 하나의 프레임에서 나머지 프레임으로 전송이 되도록 하여, 사용자가 쉽게 퍼지 논리 제어기의 수행과정을 관찰하고 이해할 수 있도록 하였다. 본 논문의 결과는 사이버 대학에서 사이버 강의의 능률을 향상시키는데 사용될 수 있다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1374-1376
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• 1996

In this paper We proposed a new method to generate fuzzy logic controllers through genetic algorithm(GA). In designing of fuzzy logic controllers encounters difficulties in the selection of optimized member-ship functions, gains and rule base, which is conventionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers which can overcome nonlinearities in many engineering control applications. The rule-base is coded in base-7 strings by generated from random function. Which can be presented in discrete fuzzy linguistic value, and using membership function with Gaussian curve. To verify the validity of this fuzzy logic controller it is compared with conventional fuzzy logic controller(FLC) and PID controller.

• 융합신호처리학회논문지
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• 제13권4호
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• pp.233-237
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• 2012

본 논문에서는 RTDNN과 FLC를 이용해서 주신경망을 보상하는 제어시스템을 제안한다. 주신경망이 학습을 완료한 후 외란이나 부하변동이 생겨 오브 슛 내지는 언더 슛을 나타낼 때 적절히 조정하기 위해 퍼지 보상기를 사용하여 원하는 결과를 얻을 수 있도록 하였다. 그리고 제어대상의 역모델 신경망에서 학습시킨 결과를 이용하여 주신경망의 가중치를 변경시킴으로서 제어대상의 원하는 동적 특성을 얻게 된다. 모의 실험 결과 제안한 신경망 제어기의 양호한 응답 특성을 확인 할 수 있다.

• 한국정밀공학회지
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• 제12권4호
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• pp.111-118
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• 1995

This paper presents the modified fuzzy-compensated PID(FCPID) control, which involves adding the compensator to an existing PID controller, to improve the performances of the systems. Compared to a conventional PID control and a fuzzy logic control(FLC), the proposed control scheme has superior performance. Experimental results of an actual implementation of the modified PC-based FCPID controller on the DC servo-motor demonstrate considerable improve- ment of the performance of the existing FCPID control by monitoring the scaling factor. They show faster responses and smaller overshoots than the conventional FCPID control scheme for the various reference inputs and the robustness to the loads.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.620-622
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• 2004

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 the floor decreases suddenly, the robot has a slip state. 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 weigh. Secondly, reposed fuzzy logic applied by the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takaki-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm controls recovered driving torque for the restrain the re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena through that compare fuzzy with PI control for the controller performance in the re-adhesion control strategy. These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.