• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.58-67
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• 1992

This paper presents a method on applying Genetric Algorithms(GA), which is a well-know high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilized Sugeno's hybrid inference method. which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the iptimal parameters in the FLC. The proposed approach will be demonstrated using 2 d. o. f robot manipulator to verify its effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1095-1103
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• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.192-199
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• 2004

Navigation simulators have been used in many marine schools and manne training centers since the early 1960's. But these simulators were very expens~ve and were almost limited only in one engine system. In this paper, a catamaran with twin engine system. controlled by two remote control levers and its economic simulator based on a personal computer shall be introduced. One of the main features of catamaran is to control variously its progressing direction. In the static state, a catamaran can move into all the directions and in the dynamic state, ship can change immediately the heading and speed. Although a good navigator can skillfully operate one engine system, it is difficult to control smoothly the catamaran of twin engine system without any threat for the safety of passengers. Thus. in order to bring up the expert navigators. the development of a simulator which makes the training effective is necessary, Therefore, in this paper, a Fuzzy Inference Technique based Maneuvering Simulator for catamaran with twin engine system was developed. In general. in order to develop a catamaran simulator for effective training, first of all. its mathematical model must be acquired. According to the acquired system modeling. the dynamics of simulator is determined, But the proposed technique can omit a complex and tedious mathematical modeling procedures by using the fuzzy inference, which dependent upon only experiences of an expert and can design an efficient training program for unskillful navigators. This developed simulator was consisted of two fuzzy inference routines and two remote control levers, and was focused on effective training of navigators for the safe maneuvering to avoid a collision in a harbor.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.233-238
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• 2002

This paper propose the construction of fault diagnosis engine for diesel generator engine and rule inference method to induce rule for fuzzy inference from the monitored data of diesel engine. The proposed fault diagnosis system is constructed the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HME), It is Proposed the rule reduction method of knowledge base for concerning data among the various analog data.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.449-455
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• 2011

In this paper, Proposed controller prevent compressor surge and reduce the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PI+D control algorithm and make an inference by applying Mamdani's inference method and the defuzzification using the center of gravity method. Fuzzy inference results are used as the fuel flow control inputs to prevent compressor surge and flame-out for turbo-jet engine and the controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.179-184
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• 1998

In this paper, a new hierarchical fuzzy inference system (HFIS) using structured Takagi-Sugeno type fuzzy inference units(FIUs) is proposed. The proposed HFIS not only solves the rule explosion problem in conventional HFIS, but also overcomes the readability problem caused by the structure where outputs of previous level FIUs are used as input variables directly. Gradient descent algorithm is used for adaptation of fuzzy rules. The ball and beam control is performed in computer simulation to illustrate the performance of the proposed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.70-77
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• 1998

Although many methods of knowledge acquisition has been developed in the exper systems field, such a need form causal knowledge acquisition hs not been stressed relatively. In this respect, this paper is aimed at suggesting a causal knowledge acquisition process, and then investigate the causal knowledge-based inference process. A vehicle for causal knowledge acquisition is FCM (Fuzzy Cognitive Map), a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain. Although FCM has a plenty of generic properties for causal knowledge acquisition, it needs some theoretical improvement for acquiring a more refined causal knowledge. In this sense, we refine fuzzy implications of FCM by proposing fuzzy causal relationship and fuzzy partially causal relationship. To test the validity of our proposed approach, we prototyped a causal knowledge-driven inference engine named CAKES and then experimented with some illustrative examples.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.61-69
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• 2001

This study concerns designing effective fuzzy inference rules, which can be used to evaluate other experiment sets for sensory tests. The number of fuzzy inference rules might be determined by the fuzzy division of variables. For the more the number of fuzzy division does not mean the more effectiveness, the number of inference rules should be reduced to improve efficiency of inference engine of expert system. This study verified that its suggested method and inference rules are effective in comparison with the existing studies.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.45-52
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• 2009

Recently, we started a project development of the digital expert system for the product design supporting in manufacturing industry. This digital expert system is used to the engineers in manufacturing industry for the process control, production management and system management. In this paper, we develop the ontology based inference engine shell for building of expert system. This expert system shell included a various functions which of Korean language supporting, graphical ontology map modeling interface, fuzzy rule definition function and etc. And, we introduce the knowledge representation method for the ontology map building and ontology based fuzzy inferencing method.