• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.916-919
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robot's work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.16-21
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• 2005

This paper considers the problem of state estimation in linear continuous-time systems with multi-sensor environment and observation uncertainties. We propose two suboptimal filtering algorithms for these types of systems. The filtering algorithms consist of two steps: The local optimal Kalman estimates are computed at the first step. And, these local estimates are lineally fused at the second step. The implementation of the two-step filtering algorithms needs a lower memory demand than the optimal Kalman and adaptive Lainiotis-Kalman filters. In consequence of parallel structure of the proposed filters, the parallel computers can be used for their design. The examples exhibit the effect of common noise on the performance of fusion of the local Kalman estimates based on observations from different sensors and in the presence of uncertainties.

• 전자공학회논문지C
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• 제35C권5호
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• pp.33-40
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• 1998

In this paper, a design of current-mode continuous-time filters for low voltage and low frequency applications using complementary bipolar current mirrors is presented. The proposed current-mode filters consist of simple bipolar current mirrors and capacitors and are quite suitable for monolithic integration. Since the design method of the proposed current-mode filters are based on the integrator type of realization, it can be used for a wide range of applications. Since the input impedance of simple bipolar current mirror is small, in this paper, negative feedback amplifier is used to realize is designed by cascade method. The cutoff frequency of the designed filter can be easily tunable by the DC controlling current from 60kHz to 120kHz. The characteristics of the designed current-mode filters are simulated and examined by SPICE using standard bipolar transistor parameters.

• 전기학회논문지P
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• 제57권2호
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.323-325
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• 1993

In this paper, an output feedback controller is proposed for continuous time-invariant linear systems. The proposed controller, LQ-FIR consists of an LQ control gain and an optimal FIR filter. The LQ-FIR controller is derived, and the stability of the closed loop system is proved. The bounds of parameter variations guaranteeing the closed loop stability are obtained, when the LQ-FIR controller is applied to the system with model uncertainties.

• Journal of Advanced Marine Engineering and Technology
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• 제24권1호
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• pp.94-103
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• 2000

This paper describes the model identification and the discrete-time sliding mode control of electro-hydraulic servo systems which are composed of servo valves, double-rod cylinder and load mass. The controlled plant is identified as a 3th-order discrete-time ARMAX model obtained from the prediction error algorithm, where a nominal model and modeling errors are zuantitatively constructed. The discrete sliding mode controller for 3th-order ARMAX model is designed in discrete-time domain, where all states are observed from Kalman filter. The discrete sliding mode controller has better tracking performance than that obtained from continuous-time sliding mode controller, in experiment.

• 한국소음진동공학회논문집
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• 제22권12호
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• pp.1227-1236
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• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

• 한국통신학회논문지
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• 제34권1C호
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• pp.72-80
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• 2009

참조표와 벡터적응필터를 이용하여 디지털 하프톤컬러영상을 역하프토닝하는 방법을 제안한다. 하프토닝은 연속계조영상을 이진영상으로 변환하는 방법이고 이진영상을 연속계조영상으로 복원하는 것이 역하프토닝이다. 일반적으로 참조표를 이용한 방법은 처리속도가 빠르고 다양한 하프토닝방식에 대해서 고른 성능을 가진다. 참조표의 패턴을 정의하기 위해 사용하는 픽셀의 개수와 R, G, B 각 채널의 참조표를 어떻게 정의하는가는 참조표의 성능에 큰 영향을 미친다. 본 논문에서는 표현 가능한 패턴의 종류와 사용되는 메모리 양을 고려하여 16개의 픽셀을 이용하고 R, G, B 각 채널의 참조표를 통합하여 하나의 참조표를 사용하는 방법을 제안하였다. 21개의 픽셀을 이용하고 R, G, B 각 채널의 참조표를 독립적으로 사용하는 기존의 참조표 방법보다. 제안된 참조표가 더 좋은 PSNR을 가지며 속도가 빨라지는 것을 실험결과를 통해 확인하였다. 참조표에 존재하지 않는 패턴에 대한 처리방법으로는 주변 픽셀의 정보를 이용하여 컬러를 복원하는 벡터적응필터를 제안하였다. 벡터적응필터는 주변 픽셀이 원영상의 컬러를 잘 반영할수록 좋은 성능을 가진다. 제안된 벡터적응필터의 성능이 기존의 방법보다 더 좋은 성능을 보임을 실험으로 확인하였다. 이를 통해서 제안된 방법이 기존의 방법보다 컬러 복원성능도 더 우수함을 알 수 있었다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권2호
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• pp.245-254
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• 2004

이 논문은 카메라가 연속적으로 움직일 때 그 카메라로부터 얻은 동영상을 분석하여 카메라의 움직임에 대한 정보와 영상내의 구조물의 삼차원 정보를 계산하는 알고리듬에 대한 것이다. 일반적으로 불 연속한 위치에서 얻은 영상의 집합으로부터 삼차원정보 및 카메라 정보를 얻는 경우에는 카메라의 움직임에 대한 제약조건이 필요 없지만, 비디오 카메라를 이용하여 동영상을 취득하는 경우에는 항상 카메라의 움직임이 부드러워야 한다는 조건이 따라 붙는다. 따라서, 이 논문에서는 ‘부드러운 움직임을 가지는 카메라’라는 제약조건을 포함하는 카메라 및 삼차원정보의 최적화 과정에 대하여 연구하였다. 목적하는 바를 얻기 위하여 Expectation-Maximization 방법을 사용하여 카메라의 움직임에 대한 모델 파라메터를 동시에 추정하였는데, 이를 위하여 Extended Kalman Filter 와 Extended Kalman Smoother를 적용하였다. 이 연구는 길이가 긴 비디오 영상열의 비젼 해석에 기본이 된다. 실제 영상을 이용하여 실험한 결과를 보였다.