• 한국펄프종이공학회:학술대회논문집
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• 한국펄프종이공학회 2004년도 춘계학술발표논문집
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• pp.97-106
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• 2004

The paper making process itself is a typical nonlinear process with complicated dynamics. In the application of advanced control-methods especially for the grade change operations the nonlinear process is linearized to give suitable linear models to be used in the control strategies. However, the use of the linear model is limited within short range containing steady-state operating conditions for grade change operation. In this paper a bilinear model for the nonlinear grade change processes is presented. We can see that the dynamic behavior for grade change operations can be effective analyzed by using multivariable bilinear model.

• 한국정보통신학회논문지
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• 제14권7호
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• pp.1544-1550
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• 2010

비선형 동적 시스템을 모델링하기 위해 GMDH(Group Method of Data Handling)를 적용한 많은 연구들이 수행되어 왔다. 그러나 모델링의 정확성을 위해서는 계산량이 크게 증가한다. 그러므로 본 논문에서는 입력 데이터를 취사선택하는 기준을 점감적으로 조정함으로써 적어도 정확성을 유지하면서 전형적인 GMDH의 단점인 과도한 계산을 피할 수 있는 방법을 제안한다. 컴퓨터 시뮬레이션 결과, GMDH 알고리듬의 계산량을 성공적으로 줄일 수 있었고 에러율도 소폭 줄일 수 있었다.

• 제어로봇시스템학회논문지
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• 제6권11호
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• pp.968-973
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• 2000

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.383-386
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• 1997

In this paper, We proposed a parallel structure of the Neural Network model to nonlinear complex system. Neural Network was used as basic model which has learning ability and high tolerence level. This paper, we used Neural Network which has BP(Error Back Propagation Algorithm) model. But it sometimes has difficulty to append characteristic of input data to nonlinear system. So that, I used HCM(hard c-Means) method of clustering technique to append property of input data. Clustering Algorithms are used extensively not only to organized categorize data, but are also useful for data compression and model construction. Gas furance, a sewage treatment process are used to evaluate the performance of the proposed model and then obtained higher accuracy than other previous medels.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권1호
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• pp.39-42
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• 2002

For the purpose of modeling EEG signal which has nonstationary and nonlinear dynamic characteristics, this paper propose a state feedback real time recurrent neural network model. The state feedback real time recurrent neural network is structured to have memory structure in the state of hidden layers so that it has arbitrary dynamics and ability to deal with time-varying input through its own temporal operation. For the model test, Mackey-Glass time series is used as a nonlinear dynamic system and the model is applied to the prediction of three types of EEG, alpha wave, beta wave and epileptic EEG. Experimental results show that the performance of the proposed model is better than that of other neural network models which are compared in this paper in some view points of the converging speed in learning stage and normalized mean square error for the test data set.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.463-465
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• 1997

For fast response of the dc output voltage in PWM converter, the relationship of power balance of both the input and output should be introduced to the system modeling. Then, a nonlinear control theory using state feedback linearization is useful to control the system. By nonlinear control, the voltage response can be fast, so the size of the output filter capacitor can be reduced as long as the same response is kept. The validity of the proposed scheme is shown from the simulation results.

• 한국CDE학회논문집
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• 제15권1호
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• pp.70-83
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• 2010

Recently, floating cranes are mainly used to erect heavy blocks or cargos for constructing ships in many shipyards. It is important to estimate the dynamic motion of the heavy cargo suspended by a floating crane and the tension of the wire ropes between the floating crane and the heavy cargo. In this paper, the coupled dynamic equations of motion are set up for considering the 6 degree-of-freedom floating crane and the 6-degrees-of-freedom heavy cargo based on multibody system dynamics. Depending on the cargo weight, the motion of the floating crane would be changed to nonlinear state. The nonlinear terms in the equation of motion are considered. In addition, the nonlinear hydrostatic force, the linear hydrodynamic force, wire rope force, mooring force and gravity force are considered as the external forces. As the result of this paper, we analyze the engineering effect for erecting the heavy cargo by using the floating crane.

• 한국자동차공학회논문집
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• 제12권3호
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• pp.170-176
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• 2004

MR dampers show highly nonlinear and histeretic dynamic behavior. Therefore, for a vehicle dynamic simulation with MR dampers, this dynamic characteristics should be accurately reflected in the damper model. In this paper, an artificial neural network technique was developed for modeling MR dampers. This MR damper model was successfully verified through a random input forcing test. This MR damper model can be used for semi-active suspension vehicle dynamics and control simulations with practical accuracy.

• 대한전기학회논문지:전력기술부문A
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• 제51권7호
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• pp.327-332
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• 2002

In this paper, conventional reactive power compensation is defined and instantaneous real control concept for shunt converters is proposed. This equipment incorporates the compensation function of harmonics at the distribution line by nonlinear load. These methodologies are applied to IEEE 13 distribution system with the modeling of nonlinear load using EMTEDC/PSCAD package. Simulation with EMTDC results presented to confirm that the new approach has better performance than those obtained by controllers based on traditional concepts of reactive power compensation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2327-2329
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• 2000

This paper addresses the use of a nonlinear modeling procedure which construct a wavelet-based fuzzy model using genetic algorithm. A fuzzy inference system has the functional equivalence with a wavelet transform. Therefore, a wavelet-based fuzzy model using GA inherits the advantage of wavelet transform. Hereby, its performance is promoted. By help of the ability of GA to search the optimum globally, parameters of wavelet transform is determined closely to the optimal point. The feasibility of the proposed fuzzy model is proved by modelling a highly nonlinear function and comparing it with previous research.