• 한국군사과학기술학회지
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• 제11권3호
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• pp.50-57
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• 2008

A telemetry ground station has a highly directional, parabolic tracking antenna to receive a weak telemetry signal from a target at a distance. The tracking antenna with narrow beam-width normally uses the auto-track method for the target tracking. This paper presents several issues in the auto-track method and introduces a new tracking method using Self-Slaving technique. Self-Slaving means that the tracking antenna is slaved to not data measured by RADAR but GPS/INS informations received by the telemetry system for pointing. The Self-Slaving method shows good performance in comparison with auto-track method.

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.510-518
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• 2004

The PID trajectory tracking controller for robotic systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point can not be defined for the control system involving performance limitation, we define newly the quasi-equilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide us the auto-tuning method for PID controller. Also, the quasi-equilibrium region is used as the target performance of auto-tuning PID trajectory tracking controller. The auto-tuning law is derived from the direct adaptive control scheme, based on the extended disturbance input-to-state stability and the characteristics of performance limitation. Finally, experimental results show that the target performance can be achieved by the proposed automatic tuning method.

• 대한의용생체공학회:의공학회지
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• 제28권3호
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• pp.363-368
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• 2007

Most surgery illumination systems have been developed as passive systems. However, sometimes it is inconvenient to relocate the position of the illumination system whenever the surgeon changes his pose. To cope with such a problem, this study develops an auto-illumination system that is autonomously tracking the surgeon's movement. A 5-DOF serial type manipulator system that can control (X, Y, Z, Yaw, Pitch) position and secure enough workspace is developed. Using 3 ultrasonic sensors, the surgeon's position and orientation could be located. The measured data aresent to the main control system so that the robot can be auto-tracking the target. Finally, performance of the developed auto-illuminating system was verified through a preliminary experiment in the operating room environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.825-830
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• 1990

This paper reports the design procedure and testing result of a servo driven pan/tilt device which is capable of tracking arbitrary movement of a specified target object. In order to achieve real-time acquisition of feedback signal, a 2 degrees-of-freedom non-contact type displacement follower is used. The performance of the system is tested for different target velocities and control gains. The result of the research may provide an effective tool for visual transfer in the context of teleoperation.

• 한국해양공학회지
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• 제36권1호
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• pp.50-60
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• 2022

The deep ocean engineering basin (DOEB) of the Korea Research Institute of Ship and Ocean Engineering (KRISO) is equipped with an extreme-environment reproduction facility that can analyze the motion characteristics of offshore structures and ships. In recent years, there have been requirements for a wide range of six-degree-of-freedom (6-DOF) motion measurements for performing maneuvering tests and free-running tests of target objects (offshore structures or ships). This study introduces the process of developing a wide-area motion measurement technology by incorporating the auto-tracking technology of the towing carriage system to overcome the existing 6-DOF motion measurement limitation. To realize a wide range of motion measurements, the automatic tracking control system of the towing carriage in the DOEB was designed as a speed control method. To verify the control performance, the characteristics of the towing carriage according to the variation in control gain were analyzed. Finally, a wide range of motions was tested using a model test object (a remotely operated vehicle (ROV)), and the wide-area motion measurement technology was implemented using an automatic tracking control system for a towing carriage.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2012년도 춘계학술대회
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• pp.573-575
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• 2012

기존 RADAR 기반의 VTS에 AIS를 연계 집약하면서 예측 불가능한 데이터 전송률에도 동일선박으로부터의 AIS 및 RADAR 데이터는 상관관계를 유지하면서 물표에 대한 Tracking이 지속적으로 이루어져야 하지만 AIS 신호 Lost시 RADAR Tracking 자동 전환이 안 되는 경우가 많이 발생하고 있다. 또한 3개의 VTS 모니터 화면에 각각 다른 Scale과 다른 관제구역이 디스플레이 됨으로써 특히 모니터 가장자리 부근의 관제구역은 사각지대로 관제사의 집중도가 떨어질 수밖에 없다. 이러한 문제점들은 관제사의 Traffic Image구성 및 Situational Awareness를 방해하는 요소로 작용하며 사고의 개연성을 높이고 있다. 본 연구에서는 VTS 모니터상의 화면 재구성 방법을 통해서 관제사의 SA를 돕고, AIS-RADAR Tracking 알고리즘 보완을 통한 Target Tracking의 안정성을 확보하고, 교육 훈련을 통해서 AIS특성과 Error현상에 대한 관제사들이 충분히 이해하도록 하여 관제업무의 향상을 기하는 방안을 제시하였다.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1999년도 학술대회논문집-국제 전기방전 및 플라즈마 심포지엄 Proceedings of 1999 KIIEE Annual Conference-International Symposium of Electrical Discharge and Plasma
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• pp.121-126
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• 1999

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed. In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the manipulator of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• 한국조명전기설비학회지:조명전기설비
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• 제13권2호
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• pp.187-187
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• 1999

in order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed. Also, the learning architecture to compute inverse kinematic coordinates transformations in the manipulator of auto-equipment system is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulation are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.77.5-77
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• 2001

A Robot vision system with a visual skill so as take information for arbitrary target or object has been applied to auto-inspection and assembling system. It catches the moving target with the manipulator by using the information from the vision system. The robot needs some information where the moving object will place after certain time. A camera is fixed on a robot manipulator, not on the fixed support outside of the robot. It secures wider working area than the fixed camera, and it dedicates to auto scanning of the object. It computes some information on the object center, angle and speed by vision data, and can guess grabbing spot by arriving time. When the location ...

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.84-86
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• 2001

A new navigation method is developed and implemented for mobile robot. The mobile robot navigation problem has traditionally been decomposed into the path planning and path following. Unlike tracking-based system, which minimize intercept time and moved mobile robot distance for optimal rendezvous point selection. To research of random moving object uses algorithm of Adaptive Control using Auto-regressive Model. A fine motion tracking object's trajectory is predicted of Auto-regressive Algorithm. Thus, the mobile robot can travel faster than the target wi thin the robot's workspace. The can select optimal rendezvous point of various intercept time.