• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.407-414
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.205-214
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• 2012

We study some properties of interval-valued fuzzy normal subgroups of a group. In particular, we obtain two characterizations of interval-valued fuzzy normal subgroups. Moreover, we introduce the concept of an interval-valued fuzzy coset and obtain several results which are analogous of some basic theorems of group theory.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.121-125
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• 2015

In this paper, we propose a method that extracts features from character patterns using the fractal dimension of chaos theory. The input character pattern image is converted into time-series data. Then, using the modified Henon system suggested in this paper, it determines the last features of the character pattern image after calculating the box-counting dimension, natural measure, information bit, and information (fractal) dimension. Finally, character pattern recognition is performed by statistically finding each information bit that shows the minimum difference compared with a normalized character pattern database.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.34-46
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• 2001

The Boolean logic analysis method using GIS as a spatial decision support system(SDSS) contains two problems. One is losing a lots of informations in analysis process, the other is unable to reflect of different weights between analysis items. The purpose of this study is to provide a new decision-making model for site analysis, that provides a rational and systemic way using fuzzy sets theory and analytic hierarchy process(AHP) theory. According to this study of technopark in Pohang, Boolean logic method did not reflect the influence of the differently weighted items and selected only 8.0% to 16.1% of the area for suitable sites for residence, commercial/research, park/green uses. The fuzzy sets theory and AHP theory method were able to reflect the influence of differently weighted items and selected 32.9% to 37.4% of the area for the best sites, and also provided more other kinds of informations. The results of this study show that GIS system using fuzzy sets theory and AHP proess method provides a more flexible and objective solutions for site analysis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.216-221
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• 2005

The rapid growth and spread of the World Wide Web has made it possible to easily access a variety of useful information. It is, however, very difficult to retrieve, manage, and use the desired information in web. Various kinds of systems such as Search engines, MetaSearch engines, Spiders, Softbots, Intelligent Agents or Web Agents have been developed by a large number of researchers and companies. Those systems as intelligent agent are employed to avoid the overload of information. To efficiently improve the Software Agents, it is necessary to represent and classify the retrieved data. And to improve performance of the Intelligent Agents to create the classification, it is offered how to evaluate the propriety with other information retrieved from the Web and to recommend to the user the most suitable information.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.4
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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 Computational Design and Engineering
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• v.2 no.3
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• pp.137-147
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• 2015

In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.385-391
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• 2008

Robotics has emerged as an important field for the future. It is our vision that robots in future will be able to transcend these precincts and work side by side humans for the greater good of mankind. We developed a face robot for this purpose. However, Life like robots demands a certain level of intelligence. Some scientists have proposed an event based learning approach, in which the robot can be taken as a small child and through learning from surrounding entities develops its own personality. In fact some scientists have proposed an entire new personality of the robot itself in which robot can have its own internal states, intentions, beliefs, desires and feelings. Our approach should not only be to develop a robot personality model but also to understand human behavior and incorporate it into the robot model. Human's personality is very complex and rests on many factors like its physical surrounding, its social surrounding, and internal states and beliefs etc. This paper discusses the development of this platform to evaluate this and develop a standard by a society based approach including the cultural paradigm. For this purpose the fuzzy control theory is used. Since the fuzzy theory is very near human analytical thinking it provides a very good platform to develop such a model.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.81-89
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• 1996

A design method of fuzzy modeling is presented for the model identification of route choice of traffic problems.The proposed fuzzy modeling implements system structure and parameter identification in the eficient form of""IF..., THEN-.."", using the theories of optimization theory, linguistic fuzzy implication rules. Three kinds ofmethod for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 21,and proposed modified-linear inference (type 3). The fuzzy inference method are utilized to develop the routechoice model in terms of accurate estimation and precise description of human travel behavior. In order to identifypremise structure and parameter of fuzzy implication rules, improved complex method is used and the least squaremethod is utilized for the identification of optimum consequence parameters. Data for route choice of trafficproblems are used to evaluate the performance of the proposed fuzzy modeling. The results show that the proposedmethod can produce the fuzzy model with higher accuracy than previous other studies -BL(binary logic) model,B(production system) model, FL(fuzzy logic) model, NN(neura1 network) model, and FNNs (fuzzy-neuralnetworks) model -.fuzzy-neural networks) model -.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.72-78
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• 2015

Alexandrov topologies are the topologies induced by relations. This paper addresses the properties of Alexandrov topologies as the extensions of strong topologies and strong cotopologies in complete residuated lattices. With the concepts of Zhang's completeness, the notions are discussed as extensions of interior and closure operators in a sense as Pawlak's the rough set theory. It is shown that interior operators are meet preserving maps and closure operators are join preserving maps in the perspective of Zhang's definition.