• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.74-77
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• 2001

One of the most important technology in PA(Factory Automation) is to construct the diagnostic system for manufacturing process. To improve the productibility in the factory, the state of tools such as bite, drill, endmill should be monitored continuously. In this study, fuzzy logic was used to check the wear of drill in drilling process. The input variables to construct the fuzzy rules are cutting force and the rate of cutting force's change. The experiment was done with the fixed spindle speed and feed rate in cutting condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.584-588
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• 1991

This paper presents a fuzzy adaptive controller which can improve the control policy automatically. Adaptation is achieved by the addition of on-line identification of the fuzzy inverse model using input-output data pairs of the process. Starting with an initial crude control rule, the adaptive controller matches the model to the process to self-tune the controller. The control algorithm needs much less memory of computer than other SOC algorithms.

• 산업경영시스템학회지
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• 제25권4호
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• pp.61-68
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• 2002

This paper provides a method of consciousness structure analysis for research and development project evaluation using fuzzy structure modeling(FSM). Fuzzy structure modeling, which is a modeling method for consciousness structure, has a large number of pairwise comparison by human subjective judgement and is difficult to check the consistency index of denoting the precision for human judgement. Thus, in this paper, we analyzed the structure of consciousness by fuzzy structural modeling method, introducing the concept of pairwise comparison matrix in Analytic Hierarchy Process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1727-1731
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• 2003

In this paper we proposed backward fuzzy Petri-net to diagnoses faults in power systems by using the time sequence information of protection system. As the complexity of power systems increases, especially in the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires new and systematic methods to the reasoning process, which improves both its accuracy and its efficiency. The fuzzy Petri-net models of protection system are composed of the operating process of protective devices and the fault diagnosis process. Fault diagnosis model, which makes use of the nature of fuzzy Petri-net, is developed to overcome the drawbacks of methods that depend on operator knowledge. The proposed method can reduce processing time and increase accuracy when compared with the traditional methods. And also this method covers online processing of real-time data from SCADA (Supervisory Control and Data Acquisition)

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.350-353
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• 2003

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experiment81 results of the simulation.

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.246-251
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• 2001

본 연구에서는 성공적인 전자상거래시스템 관리를 위하여 지능적 검색 에이전트 모델을 제안했다. 퍼지 이론은 모호한 키워드 조건에서 시스템이 검색을 수행해야 할 경우에 매우 유용한 방법이다. 따라서, 퍼지 이론을 이용하여 고객의 모호한 검색어를 효과적으로 처리할 수 있는 모델을 제안했다. 이를 통해, 다른 크리스프한 검색어 환경에서의 시스템에 비해 상대적으로 적합한 결과를 도출할 수 있음을 확인했다.

• 한국조명전기설비학회지:조명전기설비
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• 제9권4호
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• pp.103-110
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• 1995

Fuzzy theory is recently finding wide popularity in various applications that include management, economics, medicine and process control system. This paper describes application of fuzzy logic in a current control system that use a inverter welding machine. The Fuzzy control is then extended to the current loop control, replacing the conventional proportional-integral(PI) control methods. The fuzzy control algorithms have been developed in detail and verified by experiments of a inverter welding system. The experimentation study indicates the superiority of fuzzy control over the I control methods. Fuzzy control seems to have a lot of promise in the applications of welding process control system.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1132-1142
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• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.