• Journal of Power Electronics
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• 제6권3호
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• pp.235-244
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• 2006

Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.330-333
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• 2009

This paper proposes a method to estimate the flow speed of pedestrians in surveillance videos. In the proposed method, the average moving speed of pedestrians is measured by estimating the size of real-world motion from the observed motion vectors. For this purpose, pixel-to-meter conversion factors are calculated from camera geometry. Also, the height information, which is missing because of camera projection, is predicted statistically from simulation experiments. Compared to the previous works for flow speed estimation, our method can be applied to various camera views because it separates scene parameters explicitly. Experiments are performed on both simulation image sequences and real video. In the experiments on simulation videos, the proposed method estimated the flow speed with average error of about 0.1m/s. The proposed method also showed a promising result for the real video.

• 한국음향학회지
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• 제43권3호
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• pp.324-334
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• 2024

파면곡률거리추정(Wavefront Curvature Ranging, WCR)은 음파의 파면곡률로부터 음원의 거리를 추정하는 방법이다. 기존의 파면곡률거리추정은 음속을 상수로 가정하고 삼각법으로 거리를 추정한다. 이 가정 때문에 해저면반사경로가 뚜렷하게 분리되는 해양환경에서는 거리 오차가 발생한다. 거리 오차를 줄이기 위해 해양의 음속구조를 적용하고 최대우도추정(Maximum Likelihood Estimation, MLE)방법으로 거리를 추정하는 정합 파면곡률거리추정(Matched Wavefront Curvature Ranging, MWCR) 을 제안하였다. 정합 파면곡률거리추정의 시뮬레이션 결과로부터 거리 오차의 감소를 확인하였다. 향후에 실측 신호로부터 거리 추정의 신뢰성을 확인하면 소나 시스템에 적용 가능할 것이다.

• 로봇학회논문지
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• 제18권2호
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• pp.182-188
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• 2023

Due to the acceleration of an aging society, the need for lower limb exoskeletons to assist gait is increasing. And for use in daily life, it is essential to have technology that can accurately estimate gait phase even in the walking environment and walking speed of the wearer that changes frequently. In this paper, we implement an LSTM-based gait phase estimation learning model by collecting gait data according to changes in gait speed in outdoor level ground and stair environments. In addition, the results of the gait phase estimation error for each walking environment were compared after learning for both max hip extension (MHE) and max hip flexion (MHF), which are ground truth criteria in gait phase divided in previous studies. As a result, the average error rate of all walking environments using MHF reference data and MHE reference data was 2.97% and 4.36%, respectively, and the result of using MHF reference data was 1.39% lower than the result of using MHE reference data.

• 한국농림기상학회지
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• 제19권3호
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• pp.130-139
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• 2017

기상청 동네예보 풍속으로부터 농작물의 강풍피해를 예측하기 위해, 방재기상관측지점 19곳의 2012년 풍속자료를 이용하여 기상청 동네예보의 3시간 간격과 동일한 0000, 0300 ${\cdots}$ 2100 시간대의 풍속과 직전 3시간 동안의 최대풍속 간의 관계를 직선회귀식으로 표현하였다. 매 3시간 마다 추정된 최대풍속 중 가장 큰 값을 일 최대풍속으로 간주하고, 이 때의 추정오차를 정규분포와 Weibull 분포 확률밀도함수로 표현하였다. 또한 일 최대풍속과 작물 피해 임계풍속 간의 편차를 추정오차 기반 확률 분포에 적용하여 확률누적값으로 풍해 '주의보'와 '경보' 단계를 설정하였다. 19지점별 최대풍속 추정 회귀계수(a, b)와 추정오차의 표준편차 및 Weibull 분포의 모수(${\alpha}$, ${\beta}$)는 공간내삽하여 분포도로 작성하고 종관기상관측지점 4곳(순천, 남원, 임실, 장수)의 격자값을 추출하였다. 이를 이용해 2012년의 일 최대풍속을 추정하고, 배 만삼길 품종의 낙과 발생 사례에서 제시된 풍속 10m/s를 낙과 임계풍속으로 간주, 풍해 주의보와 경보를 판정하였다. 그 결과, 최대풍속 추정오차를 Weibull 분포로 표현하여 풍해 위험 정도를 판정하는 것이 정규분포만을 이용하는 것보다 더 현장에 정확한 주의보를 발령할 수 있었다.

• ETRI Journal
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• 제45권3호
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Journal of international Conference on Electrical Machines and Systems
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• 제2권2호
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• pp.184-189
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• 2013

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is applied in the proposed system. The error between the reference voltage and the voltage applied to the motor is also affect position estimation accuracy and stability, thus it is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used, and the effects of the compensation methods are discussed. The performance of the proposed sensorless control method is evaluated by experimental results.

• 전력전자학회논문지
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• 제10권5호
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• pp.436-442
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• 2005

본 논문에서는 전동기의 고성능 속도제어를 위해 필수적인 상수인 관성을 추정하는 알고리즘을 제안한다. 제안된 알고리즘은 속도관측기에서 발생되는 관성오차의 정보를 포함하고 있는 위치 오차신호를 관측하여 이를 비례적분 제어기를 사용하여 정상상태 오차를 없게 제어함으로써 관성을 추정하므로 특히, 관측기 기반 속도측정법에 쉽게 구현이 가능하다. 모의실험과 실험결과를 제시하여 추정관성이 제안된 방법에 의하여 실제값에 수렴하였으며 이에 파라 관측된 속도 역시 실제 측정된 속도와 일치하게 되었으며, 속도제어기가 설계한 응답특성을 보임을 입증하였다.

• 한국항행학회논문지
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• 제16권6호
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• pp.1123-1133
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• 2012

논문에서는 극저속 영역 및 저속 영역에서 안정적이고 동특성이 우수한 벡터제어 시스템을 구성하여, 축소차원 상태관측기를 이용한 순시속도 관측기와 극 저속 제어, 회전자 속도를 추정하는 벡터제어 시스템에 관한 방법을 제안하였다. 본 시스템에서 제안된 관측기는 축소차원 상태관측기를 부하토크 추정에 적용하여 속도추정에 이용함으로서 시스템구성을 간단히 구현 하면서도 극 저속 영역에서 정확한 순시속도 추정이 가능하였다. 또한, 시스템 잡음에 의한 영향을 줄이고, 관측기의 극을 변화시키는 일 없이 부하외란 이나 모델화 오차, 측정 잡음 등에 강인한 유도전동기 속도제어 시스템을 제시하였다.

• Journal of Positioning, Navigation, and Timing
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• 제6권1호
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• pp.17-26
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• 2017

Latency occurs in RTK, where the measured position actually outputs past position when compared to the measured time. This latency has an adverse effect on the navigation accuracy. In the present study, a system that estimates the latency of RTK and compensates the position error induced by the latency was implemented. To estimate the latency, the speed obtained from an odometer and the speed calculated from the position change of RTK were used. The latency was estimated with a modified correlator where the speed from odometer is shifted by a sample until to find best fit with speed from RTK. To compensate the position error induced by the latency, the current position was calculated from the speed and heading of RTK. To evaluate the performance of the implemented method, the data obtained from an actual vehicle was applied to the implemented system. The results of the experiment showed that the latency could be estimated with an error of less than 12 ms. The minimum data acquisition time for the stable estimation of the latency was up to 55 seconds. In addition, when the position was compensated based on the estimated latency, the position error decreased by at least 53.6% compared with that before the compensation.