• 전자공학회논문지B
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• 제29B권7호
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• pp.79-86
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• 1992

Recent research on the application of fuzzy set theory to the design of control systems has led to interest in the theory of decomposition of multivariable fuzzy systems. Decomposition of multivariable control rules is preperable since it alleviates the complexity of the problem. However inference error is inevitable because of its approximate nature. In this paper we define an index of applicability which can classify whether the Gupta et. al's method can be applied to multivariable fuzzy system or not. We also propose a modified version of the decomposition which can reduce inference error and improve performance of the system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.566-568
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• 1998

In this paper, we suggest a optimal design method of Fuzzy-Neural Networks model for complex and nonlinear systems. FNNs have the stucture of fusion of both fuzzy inference with linguistic variables and Neural Networks. The network structure uses the simpified inference as fuzzy inference system and the BP algorithm as learning procedure. And we use a clustering algorithm to find initial parameters of membership function. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance index, we use the time series data for gas furnace and the sewage treatment process.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.61-68
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• 1998

It has become important to evaluate the qualitive reliability and condition assessment of existing structural systems in order to establish a rational program for repair and maintenance. Since most of if existing structural system may suffer from defect corrosion and damage, it is necessary to account for their effects in fuzzy reliability analysis, In this paper, an attempt is made to develope a reliability analysis for damaged structural systems using failure possibility theory. Damage state is specified in terms of linguistic valiables using natural language information and numerical information, which are defined by fuzzy sets. Using a subjective condition index of failure possibility and information of the damage state is introduced into the calculation of failure probability. The subjective condition index of quantitative and qualitative analysis method is newly proposed based on the fuzzy set operations, namely logical product, drastic product, logical sum and drastic sum

• Nuclear Engineering and Technology
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• 제28권5호
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• pp.431-439
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• 1996

In the process of simplifying the complex fate of the plant into a binary state, the information loss is inevitable. To minimize the information loss, the quantification of plant safety status has been formulated through the combination of the probability density function arising from the sensor measurement and the membership function representing the expectation of the state of the system. Therefore, in this context, the safety index is introduced in an attempt to quantify the plant status from the perspective of safety. The combination of probability density function and membership function is achieved through the integration of the fuzzy intersection of the two functions, and it often is not a simple task to integrate the fuzzy intersection due to the complexity that is the result of the fuzzy intersection. Therefore, a methodology based on the Algebra of Logic is used to express the fuzzy intersection and the fuzzy union of the arbitrary functions analytically. These exact analytical expressions are then numerically integrated by the application of Monte Carlo method. The benchmark tests for rectangular area and both fuzzy intersection and union of two normal distribution functions have been performed. Lastly, the safety index was determined for the Core Reactivity Control of Yonggwang 3&4 using the presented methodology.

• 한국터널지하공간학회 논문집
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• 제12권1호
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• pp.15-29
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• 2010

스폴링 현상은 높은 현지응력하에서 확장균열의 발달로 암반공동 주변에서 발생하는 파괴형태이다. 기존 연구에 의하면 3가지 스폴링 기준은 범위로 제시되어 있어 기준자체의 애매모호함이 상존하고 있다. 본 연구에서는 퍼지확률이론을 적용한 새로운 스폴링 발생 종합 평가모델을 제안하였고 스폴링 발생현장에 평가모델을 적용한 결과 현장관측결과와 일치하는 결과를 보였으며, 정량적으로 스폴링 발생확률을 산정할 수 있었다. 특히, 3가지 스폴링 평가인자별 상대중요도를 고려한 가중치를 적용함으로써 실제 스폴링이 관측된 현장이 스폴링이 발생하지 않는 것으로 평가되는 오류를 해결하였다. 또한, Martin 등(1999)의 손상지수에 형상계수를 도입한 수정손상지수가 포함된 스폴링 평가인자를 스폴링 발생 종합 평가모델에 적용한 결과 합리적인 스폴링 발생확률을 산정할 수 있었다.

• 한국정밀공학회지
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• 제16권12호
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• pp.152-160
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• 1999

The weld quality of $CO_2$ arc welding is closely related to the arc stability. As the characteristics of the arc are excessively complex and nonlinear, it is not easy to make the arc model as mathematical form and to control the arc state to be stabilized. This paper was aimed to estimate the arc stability and to control for stabilizing the arc state in short circuit metal transfer mode of $CO_2$ arc welding. For these purposes, the behaviors of arc stability was investigated at different welding conditions using Mita's arc stability index, and the fuzzy control algorithm which uses the arc stability index as control imput and the arc voltage as control output was developed. In the control of the arc stability, the experiments of two cases were performed; the case of setting an initial welding voltage arbitrarily, the case of the step change in workpiece shape. Obtained results were as follows; Mita's arc stability index was able to be estimated qualitatively in the case of using the inverter type welding power source and the control performance for stabilizing the arc status was excellent in the case of existing step change disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.146-151
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• 1994

An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1226-1229
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• 1993

This paper proposes a new on-line fuzzy model identification(ONFID) algorithm in which the fuzzy model evaluation stage is incorporated. The fuzzy model evaluation is performed by the fuzzy equality index which is known to be a useful tool to evaluate the performance of the identified fuzzy model. Then the fuzzy model is updated according to the result of the evaluation. Proposed ONFID algorithm can sensibly identify to the system changes. To show the usefulness of the proposed algorithm, it is applied to the fuzzy model identification problem of the gas furnace and the output prediction problem of the flexible joint manipulator which is a nonlinear system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.57-62
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• 1998

This paper presents an auto tuning method of PID controller based on the application of fuzzy logic. The proposed method combined the principles of PID control with fuzzy control, which cam considerably improve the performance index of PID controller. Simulation results show that higher performance and accuracy of overall system for desired value is achieved with our manner when compared to widely-used conventional tuning method.

• 산업경영시스템학회지
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• 제25권4호
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• pp.61-68
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• 2002

This paper provides a method of consciousness structure analysis for research and development project evaluation using fuzzy structure modeling(FSM). Fuzzy structure modeling, which is a modeling method for consciousness structure, has a large number of pairwise comparison by human subjective judgement and is difficult to check the consistency index of denoting the precision for human judgement. Thus, in this paper, we analyzed the structure of consciousness by fuzzy structural modeling method, introducing the concept of pairwise comparison matrix in Analytic Hierarchy Process.