• The Journal of Korean Institute of Communications and Information Sciences
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• v.5 no.1
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• pp.49-53
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• 1980

Since Zadeh had published the fuzzy set theory at 1965, it has been applied to many fields such as realizability of communication nets, automatic control, learning systems, switching circuits. In this paper, the method of applying a fuzzy logic to a pattern classification is studied and the difference of fuzzy logic from Boolean algebra is discussed. Classfication experiment is carried out 16 persons' photos of three families by fourty male and female observers and recognition rate 94% is obtained.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.184-189
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• 2011

Generalized intuitionistic fuzzy soft set theory, proposed by Park et al. [Journal of Korean Institute of Intelligent Systems 21(3) (2011) 389-394], has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, we prove that certain De Margan's law hold in generalized intuitionistic fuzzy soft set theory with respect to union and intersection operations on generalized intuitionistic fuzzy soft sets. We discuss the basic properties of operations on generalized intuitionistic fuzzy soft sets such as necessity and possibility. Moreover, we illustrate their interconnections between each other.

• Journal of the Korean Society of Safety
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• v.14 no.1
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• pp.55-65
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• 1999

Fuzzy logic fuzzy set theory is recently getting increasing emphasis in process control applications. This paper describes application of fuzzy logic in a speed control system that uses a phase controlled bridge converter and a separately excited dc motor. The fuzzy control is used to linearize the transfer characteristics of the converter in discontinuous conduction mod occurring at light load and high speed. The fuzzy control is then extended to the current and speed control loops replacing the conventional PI control method. The control algorithms have been developed in detail and verified by simulation of a DC motor(DM) drive system. The simulation result indicates the superiority of fuzzy control over the conventional control methods. Fuzzy logic seems to have a lot of promise in the applications of power electronics.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.4
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• pp.33-43
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• 2023

In this study, it was developed and verified an application method of fuzzy-logic theory to the rating process of agricultural fill dam safety. A fuzzy-logic is very famous logical system when some decision making is made on the status of a lack of information. Three proxies were selected and configured membership functions (MFs) and these MFs were activated in the process of fuzzification procedures. Fuzzified vlaues were passed through the rule-based inference system, then fire strength could classified among cases of the rule-based inference system. To obtain final results, Mandani-type was adapted in the defuzzification process. As the results, it was shown the developed system can give a correct results that was compared with Matlab - fuzzy inference function. More ever it could perform the detailed analysis and improvement on the infrastructure safety rating process using classical diagnosis method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1808-1811
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• 1997

A position control algorithm for a flexible manipulato is stuudied. The proposed algorithm is based on a fuzzy theroy with a Steady State Genetic Algorithm(SSGA). The conventional fuzzy methods need expert's knowledges or human experiences. The SSGA, which is one of the optimization algorithms, tunes automatically the input-output membership parameters and fuzzy rules. The computer simulation is presented ot illustrate the approaches. Finally we applied a fuzzy theory with a SSGA to aposition control of a flexible manipulator.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.211-213
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• 1993

In this paper, we proposed a design method of self-learning fuzzy logic controller using fuzzy neural network. The parameters of membership function in premise are modified by descent method and also consequent parameters by learning mechanism of animal conditioning theory. The proposed method is applied to pole balancing system in order to confirm the feasibility.

• Korean Journal of Food Science and Technology
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• v.27 no.2
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• pp.164-169
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• 1995

Fictitious experiment to control extrusion process was carried out using the fuzzy theory. Algorithm of the fuzzy logic controller(FLC) was made based on the general principles of extrusion. In the simulation, at first, thickness of extrudate was measured as feedback input variable. Secondly, a set point of screw speed was determined as output variable of extruder operating condition through FLC. Finally, the thickness of extrudate was controlled as a given set point. Barrel heater was simply controlled as on/off state, which was not fuzzy controlled.

• Journal of Power System Engineering
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• v.5 no.2
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• pp.87-92
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• 2001

Automotive suspension system is a mechanism for isolation of the vibration coming from the road inputs. Recently, the electronically controlled suspension systems which may improve ride and handling performance have been developed. Here, the continuously controlled semi-active suspension system is focused. As a mechanism to control damping forces continuously, a solenoid valve is used. The modeling for the solenoid valve is introduced briefly, a vehicle dynamics modeling is constructed, and then combined system model is completed. To design the efficient control algorithm for the semiactive suspension system the knowledge based fuzzy logic is applied and the technique how to apply the sky-hook theory to the fuzzy logic is developed. Finally, to confirm the improvement of performance the computer simulation is carried out.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.265-271
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• 1997

A fuzzy logic controller (FLC) has been widely used for many applications in recent years. But the relationship between control performance and design parameters has not been handled explicity in the conventional theory of fuzzy logic control. In this paper, based on the similarity between an FLC and a variable structure control (VSC) theory, a performance evaluation of an FLC, which gives quantitative accounts on the relationship is presented. The validity of the analysis is verified through extensive computer simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.45-49
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• 1997

In this paper, we controlled a Rotary Inverted Pendulum System using Neuro-Fuzzy Controller(NFC). The inverted pendulum system is widely used as a typical example of an unstable nonlinear control system which is difficult to control. Fuzzy theory have been because membership functions and rules of a fuzzy controller are often given by experts or a fuzzy logic control system. This controller is a feedforward multilayered network which integrates the basic elements and functions of a tradtional fuzzy logic controller into a connectionist structure which has distributed learning abilities. Such NFC can be constructed from training examples by learning rule, and the structure can be trained to develop fuzzy logic rules and find optimal input/output membership functions. Using this controller, we presented the results that controlled a Rotary Inverted Pendulum System and the associated algorithms.