• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.87-100
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• 1995

In order to control systems which contain nonlinearities of uncertainties, control strategies must deal with the effects of them. Since most of control methods based on system mathematical models have been mainly developed focused on stability robustness against nonlinearities or uncertainties under the assumption that controlled systems are linear time invariant, they have certain amount of limitations to smartly improve the transient responses of systems disturbed by nonlinearities or uncertainties. In this paper, a nonlinear fuzzy PID control method is suggested which can stably improve the transient responses of systems disturbed by nonlinearities, as well as systems whose mathematical characteristics are not perfectly known. Although the derivation process is based on the design process similar to general fuzzy logic controller, resultant control law has analytical forms with time varying PID gains rather than linguistic forms, so that implementation using common-used versatile microprocessors cna be achieved easily and effectively in real-time control aspect.

• Honam Mathematical Journal
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• v.40 no.1
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• pp.27-46
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• 2018

In this paper, (E, L)-preproximity and uniformity spaces in matriod theory as a generalized to a classical proximity and Uniformity spaces introduced by Csaszar [1] is introduced. Recently, Shi [17]-[18] introduced a new approach to the fuzzification of matroids.Here introduce (E, L)-preproximity and uniformity spaces, Uniformity and strong uniformity on (E, L)-fuzzifying matroid space, Not only study the properties of this new notions, but it has been generated (E, L)-fuzzifying matroid Space from (E, L)-preproximity and uniformity spaces. Next to introduced (E, L)-preproximity continuous in (E, L)-fuzzifying matroid space and used it in more properties. Finally we solve combinatorial optimizations problem via (E, L)-fuzzifying matroid space.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.2
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• pp.67-80
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• 1995

In order to control systems which are dominantly subjected to modeling errors and uncertainties, control strategies must deal with the effect of modeling errors and uncertainties. Since most of control methods based on system mathematical model, such as LQG/LTR method, have been developed mainly focused on stability robustness, they can not smartly improve the transient response disturbed by modeling errors and/or uncertainties. In this research, a fuzzy PID control method is suggested, which can stably improve the transient responses of systems disturbed by modeling errors as well as systems not entirely using mathematical models. So as to assure the effectiveness of suggested control method, computer simulations are accomplished for some example systems, through the comparison of transient responses.

• Journal of Industrial Technology
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• v.16
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• pp.231-237
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• 1996

In this paper, the nonlinear I/O characteristic of fuzzy logic controller is analyzed by using cell concept. Sources of the nonlinearity in a fuzzy logic controller include the fuzzification, the fuzzy reasoning and the defuzzification. A closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity is analyzed with respect to the conventional PID control and the sliding mode control.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.53-66
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• 1994

In this paper, a fuzzy expert system is developed for fault diagnoisis of a drum-type boiler system in fossil power plants. The develped fuzzy espert system is composed of knowledge base, fuzzification module, knowledge base process module, knowledge base management module, inference module, and linguistic approximation module. The main objective of the fuzzy expert system is to check the states of the system including the drum level and detect faults such as the feedwater flow sensor fault, feedwater flow control valve fault, and water wall bube rupture. The fuzzy expert system diagnoses faults using process values, manipulated values, and knowledge base which is built via interviews and questionaries with the experts on the plant operations. Finally, the validity of the developed fuzzy expert system is shown via experiments using the digital simulator for boiler system is Seoul Power Plant Unit 4.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.137-155
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• 2004

Fuzzification of a fantastic filter in a lattice implication algebra is considered. Relations among a fuzzy filter, a fuzzy fantastic filter, and fuzzy positive implicative filter are stated. Conditions for a fuzzy filter to be a fuzzy fantastic filter are given. Using the notion of level set, a characterization of a fuzzy fantastic filter is considered. Extension property for fuzzy fantastic filters is established. The notion of normal/maximal fuzzy fantastic filters and complete fuzzy fantastic filters is introduced, and some related properties are investigated.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.93-98
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• 2006

The paper describes a method o( user feedback in order to enhance the retrieval system effectiveness. The existing fuzzification function adapting fuzzy technique has difficulty that 4 type graph is made each time user select components. In this paper, to overcome this weak point of feedback, we proposed the interaction function using gaussian function that gives different learning rate according to choice of components with same function. We suggest the most efficient dynamic interaction function based on comparison of retrieval performance according to parameter of function. And then, we will construct the efficient retrieval system.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.401-405
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• 2004

The paper describes a technique for building a reuse environment obtained by polling user feedback about selected reuse components in order to enhance the system effectiveness. In order to do, we use fuzzification function adapting fuzzy technique. This is made by user profile. Function modification attained by result of continuous choice of components. This method is aimed to enhance system rather than optimization about single query

• Journal of Energy Engineering
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• v.6 no.1
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• pp.19-25
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• 1997

This paper presents the short-term operation scheduling on cogeneration system connected with auxiliary equipment by using the possibility fuzzy theory. The possibility fuzzy theory is a method to obtain the possibility boundary of the solution from the fuzzification of coefficients. Simulation is carried out to obtain the boundary of heat production in each time interval. Simulation results show the flexible operation boundary to establish effectively operation scheduling.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.925-933
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• 1991

Conventional stereo matching techniques are based on the assumption that the features representing an object in left and right images have fixed attribute values. But, in fact, such features may take different values due to the practical stereo image formation and the image acquisition error, and thus the conventional techniques tend to result in the in the incorrect matching of features. In this paper, we propose a stereo matching mathod with a possibilistic view which copes with the possible variability of feature values. As a result, this method decreases the number of incorrect matching features when the values of corresponding features are somewhat large. The effectiveness of the proposed method is shown via computer simulation.