• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.769-772
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• 1995

This paper presents fuzzy control rules of automatically driving a car. Fuzzy control rules proposed are designed by investigating human experts' experiences and composed of three groups whose functions are different. According to computer simulations which let a model car pass through a curve of S type, we showed validity of fuzzy control rules suggested.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1370-1373
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• 1993

In controlling a system having many variables to control and multi objectives to satisfy such as a roof crane system, it is often difficult to obtain fuzzy If-Then rules in usual ways. As an alternative, we can more easely obtain rules in such a manner that we obtain each independent group of rules using partial variables for a partial objective. In this case, obtained rules can be conflicting with each other and conventional inference methods cannot handle such rules effectively. In this paper, we propose a roof crane controller with optimal velocity profile generator and a fuzzy logic controller with an inference method suitable for such conflicting rules.

• 한국지능시스템학회논문지
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• 제6권2호
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• pp.43-51
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• 1996

퍼지제어에서 퍼지규칙은 퍼지제어기의 제어결정을 내리는데 중요한 역할을 한다. 그래서, 제어성능은 주로 퍼지규칙의 질에 의해서 결정된다. 본 논문에서 우리는 교차와 돌연번이의 확률이 적응적으로 변화되는 유전자 알고리즘을 사용하여 퍼지규칙을 최적화 하는 방법을 기술한다. 또한 본 논문에서 우리는 플랜트의 응답을 듀개의 부분으로 나누어 제어 목적을 만족하게 하는 적합도 측정 방식을 제안한다. 좀더 빠른 해답을 얻기 위해 우리는 초기의 퍼지규칙으로 무작위적인 규칙을 사용하지 않고 자동으로 퍼지규칙을 생성하는 방법을 사용하여 초기 퍼지규칙으로 사용했다. 이렇게 얻어진 퍼지규칙이 좋은 것인지를 보여주기 위해 비선형 플랜트를 이용하여 시뮬레이션 해보았다. 시뮬레이션 결과 우리의 방법이 합리적이고 유용한 것임이 밝혀졌다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1181-1186
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• 1993

In the paper, a new design method of rule-based fuzzy modeling is proposed for model identification of nonlinear systems. The structure indentification is carried out, utilizing fuzzy c-means clustering. Fuzzy-neural networks composed back-propagation algorithm and linear fuzzy inference method, are used to identify parameters of the premise and consequence parts. To obtain optimal linguistic fuzzy implication rules, the learning rates and momentum coefficients are tuned automatically using a modified complex method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.48-53
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• 1999

The paper presents an automated method for generating fuzzy rules and fuzzy membership functions for pattern classification from training sets of examples and an application to the land-cover classification. Initially, fuzzy subspaces are created from the partitions formed by the minimum and maximum of individual feature values of each class. The initial membership functions are determined according to the generated fuzzy partitions. The fuzzy subspaces are further iteratively partitioned if the user-specified classification performance has not been archived on the training set. Our classifier was trained and tested on patterns consisting of the DN of each band, (XS1, XS2, XS3), extracted from KITSAT-3 multispectral scene. The result represents that our classification method has higher generalization power.

• 한국정보처리학회논문지
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• 제2권2호
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• pp.209-214
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• 1995

일반적으로 퍼지 시스템 모델링에 있어서, 퍼지 규칙을 인식하고 퍼지 추론의 소속함수를 조정하기란 매우 어렵다.본 논문에서는 인공신경망을 이용함으로써,자동으로 퍼지 규칙을 인식하고 동시에 퍼지 추론의 소속함수를 조정할수 있는 방법을 제시하였다. 본 모델은 역전파를 기본으로 한 알고리즘으로 학습하며,이 방법의 타당성을 로보트 매니퓰레이터를 통해 검증한다.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2004년도 추계학술발표 논문집
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• pp.171-180
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• 2004

Underground mining causes surface subsidence long after the mining operation had been ceased. Surface subsidence can be in the form of saucer-shaped depression or collapsed chimneys or sinkholes. Sinkhole formations are predominant over shallow-depth room and pillar mines having weak overburden strata. In this study, occurrences of sinkholes due to mining activity are assessed based on local geological conditions and mining parameters using fuzzy reasoning techniques. All input and output parameters are represented with linguistic hedges. Numerous fuzzy rules are developed to relate sinkhole occurrences with input parameters using fuzzy relational matrix. Based on the combined fuzzy rules, possibility of sinkhole occurrences can be ascertained once the geological and mining parameters of any area are known.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.505-507
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• 1998

In this paper, a simple hierarchical fuzzy inference system using structured Takagi-Sugeno type fuzzy inference units(SFIUs) is proposed. The number of fuzzy rules of the proposed HFIS is minimum in the sense of that only the number of partitions of each system variables, not of intermediate outputs of layered fuzzy controllers, are concerned. And resulted number of fuzzy rules is a summation of partition in each system variables. 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.

• 전자공학회논문지B
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• 제29B권9호
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• pp.76-87
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• 1992

A novel self-organizing fuzzy plus PD control algorithm is proposed, where the proposed controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the Look-Up Table(LUT) for the fuzzy control rules and to decide how much fuzzy rules are to be modifid after evaluating the control performance, respectively. And the fuzzy controller is replaced by a PD controller in a prespecified region nearby the set point for good settling actions, where gain parameters are determined by fuzzy rules based on the magnitude of error velocity at the instant when the output penetrates into the prespecified region. To show the effectiveness of the proposed controller, extensive computer simulation results as well as experimental results are illustrated for an inverted pendulum system.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권6호
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.