• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.161-165
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• 1992

The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 전력전자학술대회 논문집
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• pp.239-244
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• 1998

We propose a nonlinear feedback controller that can control the induction motors with high dynamic performance by means of decoupling of motor speed and rotor flux. A new recursive adaptation algorithm for rotor resistance which can be applied to our nonlinear feedback controller is also presented in this paper. Some simulation results show that the adaptation algorithm for rotor resistance is robust against the variation of stator resistance and mutual inductance. In addition, it is computationally simple and has small estimation errors.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2719-2724
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• 2003

In this paper, we deal with the kinematic and dynamic modeling of hybrid robotic systems that are constructed by combination of parallel and serial modules or series of parallel modules. Previously, open-tree structure has been employed for dynamic modeling of hybrid robotic systems. Though this method is generally used, however, it requires expensive computation as the size of the system increases. Therefore, we propose an efficient dynamic modeling methodology for hybrid robotic systems. Initially, the dynamic model for the proximal module is obtained with respect to the independent joint coordinates. Then, in order to represent the operational dynamics of the proximal module, we model virtual joints attached at the top platform of the proximal module. The dynamic motion of the next module exerts dynamic forces to the virtual joints, which in fact is equivalent to the reaction forces exerted on the platform of the lower module by the dynamics of the upper module. Then, the dynamic forces at the virtual joints are distributed to the independent joints of the proximal module. For multiple modules, this scheme can be constructed as a recursive dynamic formulation, which results in reduction of the complexness of the open-tree structure method for modeling of hybrid robotic systems. Simulation for inverse dynamics is performed to validate the proposed modeling algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

• 전기학회논문지
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• 제60권8호
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.

• 한국전산구조공학회논문집
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• 제25권5호
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• pp.455-463
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• 2012

본 연구에서는 부유식 해상 풍력 발전기의 로터 축과 타워 상단에 작용하는 동적 하중을 계산하였다. 부유식 해상 풍력 발전기는 부유식 플랫폼, 타워, 낫셀, 허브, 그리고 3개의 블레이드로 구성되어 있는 다물체계 시스템이다. 본 연구에서는 이들 모두를 각각 6 자유도를 갖는 강체로 가정하였다. 부유식 해상 풍력 발전기의 타워는 플랫폼에 고정되어 있고, 3개의 블레이드는 허브에 고정되어 있다. 낫셀은 타워의 상부에 회전 관절로 연결되어 있으며, 블레이드와 허브로 구성된 로터는 낫셀과 회전 관절로 연결되어 있다. 본 연구에서 부유식 풍력 발전기의 운동 방정식은 다물체계 동역학을 기반으로 한 운동방정식 구성 방법 중 하나인 recursive formulation을 이용하여 구성하였다. 외력으로는 부유식 플랫폼에 작용하는 비선형 유체 정역학 힘과 선형 유체 동역학적 힘 그리고 계류력을 고려하였고, 블레이드에 작용하는 풍력을 고려하였다. 이와 같이 구성한 운동 방정식을 해를 구하여 풍력 발전기를 구성하고 있는 각 요소들의 각 연결 부위에 작용하고 있는 구속력을 계산하였다. 그 결과, 동적 상태에서 풍력 발전기에 작용하는 하중은 정적 상태에서 풍력 발전기에 작용하는 하중보다 큰 것을 알 수 있으며, 따라서 부유식 풍력 발전기의 구조해석의 입력 값으로서 정적 하중보다 동적 하중을 고려하는 것이 더 엄격한 해석 기준이라고 할 수 있다.

• 한국전산구조공학회논문집
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• 제26권4호
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• pp.247-254
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• 2013

본 논문에서는 해상 시추작업을 위한 heave compensation system의 시뮬레이션 모델을 개발하였다. 우선 시뮬레이션을 위하여, 다물체계 동역학 커널을 개발하였다. 다물체계 동역학 커널은 입력 받은 heave compensation system 시뮬레이션 모델의 운동학적 정보를 이용하여 recursive Newton-Euler formulation 방법을 기반으로 운동방정식을 자동으로 구성하고, 수치적으로 해를 계산하는 기능을 한다. 그리고 해상 시추선에 작용하는 외력을 계산하기 위하여 유체 정역학적 힘과 유체 동역학적 힘을 계산하는 모듈을 개발하였다. 이와 같이 개발한 커널과 모듈들을 적용하여 해상 시추선의 hoisting system 동적거동 해석을 수행하고, 관절에서의 구속력을 계산하였다.

• 한국안전학회지
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• 제9권4호
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• pp.125-131
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• 1994

This paper proposes a dynamic recursive model with the effect analysis of machine state considering human factor(human skillfulness) In a single lot man-machine production system. This model obtained using Kalman Filtering Algorithm Is based on input state, output state, machine state. For sensitivity analysis, this model constructed is examined according to the impact of human skillfulness with computer simulation. The model studied in this paper has a great advance from the point of view a combination of three factors( human engineering, dynamic control theory, quality control ) and can also be extended in several applications.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.1093-1098
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• 2002

Dynamic behaviors of the Korean High-speed Train(KHST) have been analyzed to investigate the performance on the stability, the safety and the ride comfort. Multi-body dynamics analysis program using Recursive method, called RecurDyn, have been employed in the numerical simulation. To model the wheel-rail contact, the RecurDyn uses its built-in module which uses the square root creep law. The accuracy of the rail module in RecurDyn. however, decreases in the analysis of flange contact because it linearizes the shape of the wheel and rail. To solve this problem, a nonlinear contact theory have been developed that considers the profiles of the wheel and rail. The results show that the KHST still needs more stability. The problem should be solved by the examinations of module and modeling.

• Communications for Statistical Applications and Methods
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• 제25권1호
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• pp.29-42
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• 2018

We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.