• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권3호
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.687-692
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• 1991

To reduce the complexity in constructing a fuzzy logic controller of multivariable systems, three major methods are presented. One is the method of constructing single-input-single-output fuzzy logic controllers after decoupling the target system. Another is the method of using fuzzy relation matrices which indicate the relation between each input and output. The other is the method of using the hierarchically classified inputs which dominantly influence one output than other inputs. Using the last two methods, simulation results of fuzzy logic controller implemented on 160MW boiler-turbine plant model are also shown.

• Journal of information and communication convergence engineering
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• 제1권3호
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• pp.157-162
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• 2003

We propose a learning method for improving the performance of the backpropagation algorithm. The proposed method is using a fuzzy logic system for automatic tuning of the learning rate of each weight. Instead of choosing a fixed learning rate, the fuzzy logic system is used to dynamically adjust the learning rate. The inputs of fuzzy logic system are delta and delta bar, and the output of fuzzy logic system is the learning rate. In order to verify the effectiveness of the proposed method, we performed simulations on the XOR problem, character classification, and function approximation. The results show that the proposed method considerably improves the performance compared to the general backpropagation, the backpropagation with momentum, and the Jacobs'delta-bar-delta algorithm.

• International Journal of Precision Engineering and Manufacturing
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• 제6권2호
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• pp.40-45
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• 2005

This paper has presented an application of an optimum grinding conditions based on the fuzzy logic. Fuzzy logic can handle vague and uncertain knowledge, and presents a scheme for integrating data with various kinds of grinding data. Especially, this research is capable of determining the grinding conditions taking into account some fuzzy membership function represented for trapezoidal form such as hardness and surface roughness of workpiece, material tensile strength and elongation, and requirement of grinding method. Larsen's fuzzy production method utilizing the fuzzy production rule can be applied on the establishment of grinding conditions, and also the output value obtained by the center of gravity method can effectively utilize the optimum grinding conditions.

• 한국정보과학회논문지:정보통신
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• 제31권3호
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• pp.289-297
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• 2004

최신 무선 통신망은 이동 단말의 동적 재배치를 허용하므로 입력 호를 전달하기 위해서는 이동 단말의 트랙을 관리하는 위치 관리 메커니즘이 필요하다 본 논문에서는 페이징 비용을 감소시키기 위하여 퍼지 논리 기반 선택적 페이징 방법을 제안한다. 퍼지 논리 기반 위치 관리 방법에서, 위치 갱신은 방향 기반 방법과 이동 기반 방법을 혼용한 지역 기반 방법을 사용하고, 위치 검색은 이동 단말의 이동성 정보에 기초한 퍼지 논리 기반 선택적 페이징 방법을 사용한다. 부분 후보 페이징 지역이 퍼지 논리 제어에 의해 선택되고, 퍼지 논리 기반 선택적 페이징 방법은 그 부분 후보 페이징 지역 내의 셀들만 페이지 한다. 제안하는 퍼지 논리 기반 위치 관리 방법의 성능을 분석적 모델과 모의실험을 통하여 평가하고, 그것의 성능을 LA 및 BVP와 비교한다. 평가 결과, 제안하는 퍼지 논리 기반 위치 관리 방법이 다른 위치 관리 방법에 비해 우수한 성능을 제공함을 알 수 있었다.

• 대한전기학회논문지:전력기술부문A
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• 제48권2호
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• pp.145-152
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• 1999

This paper presents an optimal design method for fuzzy logic controllers using genetic algorithms. In general, the design of fuzzy logic controllers has difficulties in the acquisition of exper's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored, and parameters of the fuzzy logic controller obtained by expert's control action may not be global. To solve these problems, the proposed method using genetic algorithms in this paper, can tune the parameters of fuzzy logic controller including scaling factors and determine the appropriate number of fuzzy reles systematically and automatically. We provide the second drder dead time plant and inverted pendulum system to evaluate the feasibility and generality of our proposed method. Comparison shows that the proposed controller can producd higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controller.

• 제어로봇시스템학회논문지
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• 제13권4호
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• pp.352-357
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• 2007

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.28-31
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• 1997

This paper describes the quick and precise controlling method for home-applied refrigerator. The proposed controller is based on the fuzzy logic control method and is designed for better performance in maintaining the constant temperature of the refrigerator. The temperature of the refrigerator is controlled by the cooling air blowing fan motor which is put on, off according to fuzzy logic controller. Finally, I study the performance of the proposed controller through the computer simulation about the approximated model of the refrigerator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.326-328
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• 1998

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. The fuzzy logic controllers has been applied to a power system stabilizing controllers. But the design of a fuzzy logic power system stabilizer relies on empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents the optimal design method of the fuzzy logic stabilizer using the genetic algorithm, which is the optimization method based on the mechanics of natural selection and natural genetics. The proposed method tunes the parameters of the fuzzy logic stabilizer in order to minimize the consuming time during the design process. In this paper, the proposed method tunes the shape of membership function of the fuzzy variables. The proposed system is applied to the one-machine infinite-bus model of a power system. Through the case study, the efficiency of the fuzzy stabilizing controller tuned by genetic algorithm is verified.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.50-54
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• 1997

In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge. So, some methods that can optimize the parameters for fuzzy logic controller automatically without expert knowledge was provided. Recently, tuning method for fuzzy logic controller using genetic algorithm(GA) were proposed in many papers. However, those are tuning methods for a part or some part of fuzzy logic controller. In this paper, we proposes auto tuning method for the whole part of tuzzy logic controller, such as parameters of membership functions for antecedence and consequence parts, rule base, scaling factor and the number of rule. Finally, second order dead time plant is provided to show the advantages of the proposed method.