• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.106-116
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• 1998

A position control algorithm of a flexible manipulator is studied. The proposed algorithm is based on an ACFAC(Automatic Constructed Fuzzy Adaptive Controller) system based on the neural network learning algorithms. The proposed system learns membership functions for input variables using unsupervised competitive learning algorithm and output information using supervised outstar learning algorithm. ACFAC does not need a dynamic modeling of the flexible manipulator. An ACFAC is designed that the end point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by error, velocity and variation of error. Simulation and experiment results show a robustness of ACFAC compared with the PID control and neural network algorithms.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.361-369
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• 2006

This study conducted an initialization test to decide dynamic position using AHRS IMU sensor, and derived attitude correction angles of vehicles against time through regression analysis. It was also found that the heading angle was stabilized with variation less than 1°after 60 seconds. Using these angles, this study carried out an experiment on the determination of dynamic position for each system in the open sky and in a semi-open sky. According to the results, in the open sky, DGPS alone systems were excellent in accuracy but poor in data acquisition, so the moving distance was around 12m. In DGPS/IMU combined system, accuracy and data acquisition were satisfactory and the moving distance was around 0.3m. In a semi-open sky, DGPS alone systems were excellent in accuracy in order of DGPS < FIMU < DGPS/IMU according to average and standard errors obtained with exclusion of places where data were not be obtained. The moving distance was the same as that in the open sky. For DGPS, when places where data were not obtainable were divided into Several block and they were compared, the maximum deviation from the trajectory was up to 41.5m in DGPS alone system, but it was less than 2.2m and average and standard errors were significantly improved in the combined system. When the navigation system was applied to surveys and the result was compared with position error 0.2mm under the guideline for digital map, it was possible to work on maps on a scale of up to 1 : 1,000.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.863-870
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• 2015

A Compensation Algorithm for The Position of the User Hands based on the Moving Mean-Shift ($CAPUH_{MMS}$) in Human Robot Interface (HRI) System running the Kinect sensor is proposed in order to improve the performance of the gesture recognition is proposed in this paper. The average error improvement ratio of the trajectories ($AEIR_{TJ}$) in left-right movements of hands for the $CAPUH_{MMS}$ is compared with other compensation algorithms such as the Compensation Algorithm based on the Compensation Algorithm based on the Kalman Filter ($CA_{KF}$) and the Compensation Algorithm based on Least-Squares Method ($CA_{LSM}$) by the developed realtime performance simulator. As a result, the $AEIR_{TJ}$ in up-down movements of hands of the $CAPUH_{MMS}$ is measured as 19.35%, it is higher value compared with that of the $CA_{KF}$ and the $CA_{LSM}$ as 13.88% and 16.68%, respectively.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.161-164
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• 1999

본 논문에서는 표적 추적 시스템에서 센서 어레이에 입사되는 표적신호에 대한 센서 출력 신호간의 지연시간 추정(TDE:Time Delay Estimation)을 위해 백색상호 상관법(CSP:Cross-Power Spectrum Phase Analysis)을 이용한다. 그러나 음파의 다중경로 전달특성 및 배경잡음의 영향으로 인해 CSP계수는 많은 클러터(Clutter)를 포함하게 되고 결국 방위 추정 오차의 요인이 된다. 따라서 센서 어레이 중심좌표를 기준으로 대칭 배열된 센서쌍(Pair)에 대한 CSP계수를 동기가산 하여 실제 표적 방향 이외의 방향정보를 제거하는 방법을 제안한다. 시간에 따라 각도를 변침하는 표적에 대한 표적기동분석 (BOTMA:Bearings Only Target Motion Analysis)을 위해 매 관측시간마다 동기가산을 행한 CSP결과를 누적하여 방위각 궤적을 형성하였을 때 시간 Window에 따라 약간의 차이는 있지만 약 10dB의 궤적 추적 성능을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.1-9
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• 2000

In this paper, we design a robust output feedback controller for robot manipulators with bounded parametric uncertainties using high-gain observer. The proposed control scheme with integral action improves tracking error due to limit of the robust feedback gains. High-gain observer is used to solve the noise problem with the joint velocity measurement. This controller avoids the limitation on the variation of unknown parameters and guarantees the uniformly ultimate boundedness of the closed-loop system. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.150-159
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• 2010

The approach and landing phase of a re-entry vehicle is composed of Steep Glideslope phase, Circular Flare phase, Flare Maneuver phase. The trajectory planning algorithm with geometric parameters is studied in this paper for on-board trajectory planning. This algorithm generate reference trajectory rapidly considering safe landing of re-entry vehicle. In this paper, the Mamdani Fuzzy PD type controller for longitudinal and lateral control is designed which has robustness of nonlinear system. In addition, the simulation is performed including initial downrange and crossrange errors, and the results shows that the proposed fuzzy logic controller has good performance.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.300-312
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• 2009

An indoor location-based service cannot be realized unless the indoor positioning problem is solved. However, the cost-effective indoor positioning systems are suffering from their inaccurateness. This paper proposes a map information-based correction method for the indoor positioning systems. Using our Kalman filter with map information-based appropriate parameter values, our method estimates the track of the moving object, then it performs the Frechet Distance-based map matching on the obtained track. After that it applies our real time correction method. In order to verify efficiency of our method, we also provide our test results.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.693-698
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• 2004

In this paper, an iterative learning control method is applied to suppress a vibration of a 2-mass system which has a flexible coupling between a load and a motor. More specifically, conditions for the load speed without vibration are derived based on the steady-state condition. And the desired motor position trajectory is synthesized based on the relation between the load and motor speed. Finally, a PD-type iterative learning control law is applied for the desired motor position trajectory. Since the learning law applied for the desired trajectory guarantees the perfect tracking performance, the resulting load speed shows no vibration even when there exist model uncertainties. A modification to the learning law is also Presented to suppress undesired effects of an initial position error, The simulation results show the effectiveness of the proposed learning method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.5
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• pp.533-541
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• 2011

This paper presents a frequency-response test performed on an antagonistic actuation system consisting of two Mckibben pneumatic artificial muscles and a pneumatic circuit with pressure valves. Varying switching frequency to pressure valves from 0.1 Hz to 5 Hz, parameters of a linear model were estimated optimally to predict dynamic characteristics of the antagonistic actuation. A model-base control scheme with estimated parameters was built for the precise trajectory tracking of the antagonistic structure and realized on a reconfigurable embedded control system, CompactRIO. Experimental results showed that the proposed model-based control scheme gave good performance in trajectory tracking comparing with a PD control scheme when square wave and sinusoidal wave were given as references to follow.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.906-912
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• 2014

The study of fish robot is a main subject that are related with the propulsive force comparison using a varying amplitude and frequency for body and tail motion trajectory, and the quick turn using a proper trajectory function. In this study, when a fish robot thrusts forward, feedback control is difficult to apply for a fish robot, because body and tail joints as a sine wave are rolled. Therefore, we detect the virtual position based on the path of the fish robot, define the angle errors using the detected position and the look-ahead point on the given path, and design a controller to track given path. We have found that the proposed method is useful through the computer simulations.