• 대한기계학회논문집A
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• 제21권1호
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• pp.164-172
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• 1997

Two parameter technique that uses far-field stress and displacement distributions was applied to composite laminates in order to calculate mode II energy release rate, $G_{II}$ . The $G_{II}$ calculated by two parameter technique was compared with that calculated from the crack closure method to inspect the effectiveness of two parameter technique. Sensitivity study of two parameter technique to the crack extension size was also performed. The results showed that both methods produced comparable $G_{II}$ results. In particular, it was found that although the crack closure method was affected by the crack extension size, the two parameter technique was less affected by the crack extension size.

• 한국컴퓨터그래픽스학회논문지
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• 제17권1호
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• pp.1-7
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• 2011

본 논문에서는 2-변수 모션 (two-parameter motion)을 이용한 새로운 스윕곡면의 생성 및 편집기법을 제시한다. 먼저, 하나의 변수로 매개화되는 기존의 모션에서 방향곡선 (orientation curve)과 크기 변환곡선 (scaling curve)을 곡면의 형태로 확장한 2-변수 모션의 개념을 소개하고, 이를 이용한 새로운 스윕곡면을 제안한다. 제안된 스윕곡면은 하나의 정점이 2-변수 모션에 적용된 결과이며, u-방향의 등위곡선 (iso-curve)이 매개변수 ${\upsilon}$에 따라 다른 형상을 갖게된다. 또한 이에 대한 효율적인 모델링 및 편집기법은 2-변수모션의 직관적인 제어를 통해서 이루이진다. 본 논문에서는 복잡한 형상에 대한 모델링 및 편집 실험을 통해서 제안된 기법의 효율성 및 편리성을 입증한다.

• 한국생산제조학회지
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• 제9권2호
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• pp.112-118
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• 2000

This paper deals with the application of sensitivity method to the parameter estimation for the dynamic analysis of gener-al mechanical system. In this procedure we take the derivatives of the given system with respect to a certain parameter and use this information to implement the steepest descent method. This paper will give two examples of this technique applied to simple vehicle models. This paper will give two examples of this technique applied to simple vehicle models. Simulation results show excellent convergence and accuracy of parameter estimates.

• Communications for Statistical Applications and Methods
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• 제25권4호
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• 제어로봇시스템학회논문지
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• 제22권2호
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• pp.126-132
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• 2016

The root-locus method is often employed when a controller is designed to find controller gain. It is usually used to determine one parameter gain while most controllers for industrial applications have more than one controller gain. For example PID controller has three controller gains, i.e. P, I, and D gains. Thus the conventional root-locus technique cannot complete the design of a controller with more than one controller gain. One way to overcome this drawback has been to apply the root-locus technique for one parameter while other parameters are assumed to be proportional to the parameter or to be constant. However this approach could lead to limited performance of the controller and if we try to adjust the proportional ratio or constants then it could be a long and tedious process of trial and error. Thus it is required to find an effective method for the root-locus technique to design controllers with more than one parameter. To this end this paper proposes an extended root-locus method for controllers with two parameters. In this paper Matlab is used as a computation tool to show the effectiveness of our method by solving examples numerically. As a result we obtained an extended root-locus illustrated in two-dimensional space for a control system with two parameters. The paper then presents how to find two controller gains based on this result of the extended root-locus. The main idea is that we can find the parameters by approaching the desired poles. It is expected that the proposed idea will help control engineers to easily design control systems using the root-locus technique, resulting in more accurate and faster control systems. Note that the extended root-locus idea can be applied to controller design problems with multiple parameters.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• 한국정밀공학회지
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• 제25권10호
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• pp.67-76
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• 2008

In this research, a simple technique for designing PID controller, which guarantees robust stability for two-mass systems with parameter uncertainties as well as rigid-body behavior and zero steady-state error,is described. As well, such a PID controller is designed to mate two important frequencies, at which the given system is excited, very close so that an appropriate reference profile generated by using command shaping techniques can cover those two frequencies. Root-locus analysis. which shows traces of closed-loop poles for the given system, is used to design this PID controller. Finally, feedforward controller is added to improve tracking performance of the closed-loop system. Simulation for a system with a flexible mode and parameter uncertainties is executed to prove the feasibility of this technique.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.587-590
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• 2000

An estimation scheme is used for solving two practical problems of the single current sensor technique. To improve the effect of parameter uncertainties the method that identifies motor parameters for AC motor drive systems using the single current sensor technique is presented. And the parameter identification error and its cause atre examined. It gives good performances for identify in parameters and reconstructing phase currents.

• International Journal of Aeronautical and Space Sciences
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• 제2권2호
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• pp.73-81
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• 2001

This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.