• 조명전기설비학회논문지
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• 제26권5호
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• pp.40-47
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• 2012

The PMSM position sensor using two rectangular hall sensors can restrictively acquire the 90[$^{\circ}$] position information of rotor according to electrical angle. Thus, the control method using this position sensor cannot react properly to a rapid load torque change. On the other hand, even though a sensorless method has the advantage of acquiring instantaneous rotor position information, the accuracy of position sensor can be determined by the gain value of estimator. This paper suggests a robust speed control method on torque fluctuation condition, which combines low cost two rectangular hall sensors and sensorless control method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 B
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• pp.384-386
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• 2000

This paper describes a new approach to estimating permanent magnet synchronous motor(PMSM) speed and position from measured terminal voltages and currents for speed-sensorless vector control. The proposed system is based on observing the instantaneous reactive power of the motor. The described technique is very simple and robust to variations of motor parameters. The new approach is not dependent upon the value of the stator resistance. Also, MRAS schemes are chosen for determining the adaptive law for the speed and the position estimator. The effectiveness is verified by the experimental results.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.149-161
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• 2019

In this article, we suggest the following approaches to simultaneous variable selection and outlier detection. First, we determine possible candidates for outliers using properties of an intercept estimator in a difference-based regression model, and the information of outliers is reflected in the multiple regression model adding mean shift parameters. Second, we select the best model from the model including the outlier candidates as predictors using stochastic search variable selection. Finally, we evaluate our method using simulations and real data analysis to yield promising results. In addition, we need to develop our method to make robust estimates. We will also to the nonparametric regression model for simultaneous outlier detection and variable selection.

• 센서학회지
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• 제28권4호
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

• 한국산업융합학회 논문집
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• 제25권2_2호
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• pp.193-198
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• 2022

In this paper, we introduce the improved control method are communicated between a master and a slave robot in the teleoperation systems. When the master and slave robots are located in different places, time delay is unavoidable under the network environment and it is well known that the system can become unstable when even a small time delay exists in the communication channel. The time delay may cause instability in teleoperation systems especially if those systems include haptic feedback. This paper presents a control scheme based on the estimator with virtual master model in teleoperation systems over the network. As the behavior of virtual model is tracking the one of master model, the operator can control real master robot by manipulating the virtual robot. And LQG/LTR scheme was adopted for the compensation of un-modeled dynamics. The approach is based on virtual master model, which has been implemented on a robot over the network. Its performance is verified by the computer simulation and the experiment.

• Communications for Statistical Applications and Methods
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• 제31권1호
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• pp.155-178
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• 2024

Regression discontinuity (RD) design is one of the most widely used methods in causal inference for estimation of treatment effect when the treatment is created by a cutpoint from the covariate of interest. There has been little attention to RD design, although it provides a very useful tool for analysis of treatment effect for censored data. In this paper, we define the causal effect for survival function in RD design when the treatment is assigned deterministically by the covariate of interest. We propose estimators of this causal effect for survival data by using transformation, which leads unbiased estimator of the survival function with local linear regression. Simulation studies show the validity of our approach. We also illustrate our proposed method using the prostate, lung, colorectal and ovarian (PLCO) dataset.

• 대한수학회지
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• 제61권3호
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• pp.427-444
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• 2024

The matrix completion problem is to predict missing entries of a data matrix using the low-rank approximation of the observed entries. Typical approaches to matrix completion problem often rely on thresholding the singular values of the data matrix. However, these approaches have some limitations. In particular, a discontinuity is present near the thresholding value, and the thresholding value must be manually selected. To overcome these difficulties, we propose a shrinkage and thresholding function that smoothly thresholds the singular values to obtain more accurate and robust estimation of the data matrix. Furthermore, the proposed function is differentiable so that the thresholding values can be adaptively calculated during the iterations using Stein unbiased risk estimate. The experimental results demonstrate that the proposed algorithm yields a more accurate estimation with a faster execution than other matrix completion algorithms in image inpainting problems.

• 응용통계연구
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• 제27권3호
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• pp.397-406
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• 2014

최소밀도함수승간격 추정법은 Baus 등 (1998)에 의해 처음 소개된 이후 많은 관심의 대상이 되었다. 최소밀도함수승간격 추정량은 우수한 로버스트 성질을 갖고 효율성도 최우추정량에 필적한 것으로 알려져 있다. 본 논문에서는 생물정보학에서 사용되는 노말-지수 분포에 근거한 추정량을 최소밀도함수승간격 추정법을 사용하여 구하는 방법을 다루고자 한다. 그런데 그 과정에서 간격을 적분을 통해 구하는 것이 매우 어려움으로 인해 직접적인 적분 대신 라플라스 근사를 시도할 것을 제안한다. 그 결과 추정량이 다소 효율성이 줄어들지만 로버스트 성질을 갖고 있음을 수학적 방법과 모의실험을 통하여 보였다.

• 한국통신학회논문지
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• 제33권4A호
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• pp.434-439
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• 2008

본 논문은 2세대 위성방송용 표준인 DVB-S2 (Digital Video Broadcasting - Second Generation) 에서 사용하는 대략적 주파수 동기회로를 효율적으로 설계하는 방법을 제안한다. DVB-S2에서 제거해야 하는 대략적인 주파수 오차는 심볼 전송률의 6.25%에 해당하며 심볼 전송률이 25Mspa일 경우 ${\pm}1.5625Mhz$에 달한다. 대략적인 주파수 오차 추정을 위한 데이터 도움방식 (Data-Aided) 의 알고리즘들을 분석하여 L&R (Luise & Reggiannini) 알고리즘이 복잡도와 추정성능 면에서 가장 효율적임을 밝혔다. 그러나 L&R 알고리즘도 여전히 곱셈기와 덧셈기를 다량으로 사용하므로 구현 복잡도가 매우 높다. 본 논문은 버퍼와 멀티플렉서를 이용한 직렬 상관도 연산구조를 제안한다. 제안된 구조는 기존의 구현 방법에 비해 하드웨어 복잡도가 약 92%정도 감소되었다. 제안된 구조는 Xilinx Virtex II FPGA에서 구현되어 검증되었다.

• 한국콘텐츠학회논문지
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• 제10권7호
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• pp.10-22
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• 2010

본 논문은 시점을 달리 하는 두 이미지 사이의 다중 호모그래피 관계를 RANSAC을 이용하여 동시에 추정하는 새로운 방안을 제안한다. 이상치가 많이 포함된 데이터에 대해서도 강건한 파라미터 추정이 가능한 RANSAC 알고리즘은 단일 모델에 대해서만 적용되는 제약을 가진다. 따라서, 이미지에 존재하는 여러 평면의 2D 투영 변환 관계들을 추정하기 위해서는 RANSAC 알고리즘을 순차적으로 수행해야 한다. 이 과정에서 데이터에 지속적으로 포함되는 이상치들은 모델 추정을 느리게 한다. 또한, 모델들은 적합치 비율에 의해 순차적으로 추정되기 때문에 알고리즘의 병렬화가 어렵다는 문제가 있다. 본 논문에서는 RANSAC 알고리즘의 수행 과정에서 찾아낸 부분적인 모델 관계를 이용하여 반복 시도 횟수를 줄이고 다중 호모그래피들을 동시에 추정할 수 있는 가이드된 순차 RANSAC 알고리즘을 제시한다.