• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1055-1063
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• 1999

This paper present a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the given reliability input date of the practical power system. In this paper, an algorithm is introduced to calculate the possibilstic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilstic representation using the probability-Possibility Consistency principle(PPCP) algorithm. In this the algorithm, the transformation is performation by making a compromise between the transformation consistency and the human updating experience. Fuzzy classifcation theory is applied to reduced the number of load data. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determening the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1002-1005
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• 1991

It is important to express the specific growth rate of a fermentation reaction as a function of substrate and product concentration in developing bioprocess automation techniques such as modeling of the reactor and controlling it via an advanced control scheme. Typical methods of identification utilize graphical representation of the rate constant data or nonlinear regression with an appropriate noise filter. But the former method fails when the data are erroneous and the latter are mathematically complicated to apply in the field. Neural network is another candidate for the identification from time series data since it is insensitive to the random data error and easy to implement. In this study, we will develop a neural network method of specific growth rate estimation from the time series state variable data and test the performance.

• 전자공학회논문지A
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• 제32A권1호
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• pp.45-52
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• 1995

A new Kirchhoff approximation(KA) method was proposed for microwave scttering from randomly rough surfaces. Using the spectral representation of delta function and its sifting theorem, a new KA was formulated directly without any further approximation, and this formulated was used to compute exact backscttering coefficients. The validity of the KA was verified by a numerical method, and this new KA technique was used to evaluate the existing approximated KkA methods; i.t., the zeroth-order and the first-order approximated physical optics(PO) models. It was shown that the first-order approximated PO model has small error than the zeroth-order approximated PO model at low incidence angles and the opposite happens at higher incidence angles. This new KA model can be used to compute exact scattering coefficients in the validity regions of KA and to evaluate other theoretical and numerical models for scattering from randomly rough surfaces.

• 한국수산과학회지
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• 제48권2호
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• pp.221-232
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• 2015

Broadband echoes measured in live chub mackerel Scomber japonicus, goldeye rockfish Sebastes thompsoni, and fat greenling Hexagrammos otakii with different morphologies and internal characteristics were analyzed in time and frequency domains to understand the species-specific echo feature characteristics for classifying fish species. The mean echo image for each time-frequency representation dataset obtained as a function of orientation angle was extracted to mitigate the effect of fish orientation on acoustic scattering. The joint time-frequency content of the broadband echo signals was obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The SPWVDs were analyzed for each echo signature of the three fish species. The results show that the time-frequency analysis provided species-specific echo structure patterns and metrics of the broadband acoustic signals to facilitate fish species classification.

• 대한기계학회논문집A
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• 제28권7호
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• pp.970-976
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• 2004

For a long time, design methodologies strive to systematize the design process in order to make the practice more efficient and effective. One of such methodologies is Axiomatic Design. However, this design theory still has some problems and is not completely settled. In this paper, the new issue for the non-linear design in Axiomatic Design is suggested and the representation of system architecture by flow chart is corrected. In the case that the design equation varies as a function of the variation of DP ($\delta$DP), the design should be regarded as the nonlinear design because the design equation is not a constant. When system architectures are represented by a flow chart, all systems could not be independently represented. However, by adding the notation of the end of decoupling to the notations using in flow chart, those can be independently represented.

• Structural Engineering and Mechanics
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• 제5권3호
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• pp.221-237
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• 1997

This paper presents a new uniaxial material model for rate-sensitive analysis addressing both the transient and steady-state responses. The new model adopts visco-plastic theory for the rate-sensitive response, and employs a three-parameter representation of the overstress as a function of the strain-rate. The third parameter is introduced in the new model to control its transient response characteristics, and to provide flexibility in fitting test data on the variation of overstress with strain-rate. Since the governing visco-plastic differential equation cannot be integrated analytically due to its inherent nonlinearity, a new single-step numerical integration procedure is proposed, which leads to high levels of accuracy almost independent of the size of the integration time-step. The new model is implemented within the nonlinear analysis program ADAPTIC, which is used to provide several verification examples and comparison with other experimental and numerical results. The companion paper extends the three-parameter model to trilinear static stress-strain relationships for steel and concrete, and presents application examples of the proposed models.

• Earthquakes and Structures
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• 제7권6호
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• pp.1025-1044
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• 2014

In this paper, a systematic technique is proposed for the optimal placement and design of nonlinear dampers for building structures. The concept of Output Frequency Response Function (OFRF) is applied to analytically represent the output frequency response of a building frame where nonlinear viscous dampers are fitted for suppression of vibration during earthquakes. An effective algorithm is derived using the analytical representation to optimally determine the locations and parameters of the nonlinear dampers. Various numerical examples are provided to verify the effectiveness of the optimal designs. A comparison of the vibration suppression performance with that of the frame structure under a random or uniform damping allocation is also made to demonstrate the advantages of the new designs over traditional solutions.

• 전자공학회논문지B
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• 제32B권3호
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• pp.130-138
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• 1995

In this paper, a Novel Approach is Proposed which Identifies linear system Parameters Using a multilayer feedforward neural network trained with backpropagation algorithm. The parameters of linear system can be represented by x9t)/x(t) and x(t)/u(t). Thud, its parameters can be represented in terms of the derivative of output with respect to input of parameters can be represented in terms of the derivative of output with respect to input of trained neural network which is a function of weights and output of neurons. Mathematical representation of the proposed approach is derived, and its validity is shown by simulation results on 2-layer and 3-layer neural network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.157-160
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• 1995

Neural networks potentially offer a general framework for modeling and control of nonlinear systems. The conventional neural network models are a parody of biological neural structures, and have very slow learning. In order to emulate some, dynamic functions, such as learning and adaption, and to better reflect the dynamics of biological neurons, M.M.Gupta and D.H.Rao have developed a 'dynamic neural model'(DNU). Proposed neural unit model is to introduce some dynamics to the neuron transfer function, such that the neuron activity depends on internal states. Numerical examples are presented for a model system. Those case studies showed that the proposed DNU is so useful in practical sense.

• 조명전기설비학회논문지
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• 제17권5호
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• pp.88-93
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• 2003

본 논문에서는 반복법에 의한 쌍선형 시스템의 제어기 설계방법을 제안한다. 보조수열을 갖는 반복과정은 쌍선형 시스템으로부터 선형시변 시스템을 구성하는 과정에서 정의되고, 최적의 2차 가격함수를 갖는 쌍선형 시스템에서 궤환 제어기를 설계하기 위한 최적화 과정이 Riccati 접근법과 관련된 표현에 의해 주어진다. 제안된 방법에 의해서 개선된 성능과 우수한 수렴성이 성취됨을 시뮬레이션 결과에서 보인다.