• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.249-253
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• 2004

This paper presents an implementation of position control system of Switched Reluctance Motor (SRM) using digital hysteresis controller. Although SRM possess several advantages including simple structure and high efficiency, the control drive system using power semiconductor device is required to drive this motor. The control drive system increases overall system cost. To overcome this problem and increase the application of SRM, it is needed to develope the servo drive system of SRM. So, the position control system of 1 Hp SRM is developed and evaluated by adaptive switching angle control. The position/speed response characteristics and voltage/current waveforms are presented to prove the capability of SRM for a servo drive application. Moreover, digital hysteresis current controller is developed and evaluated by experimental testing for the purpose of system developmental cost reduction.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1332-1335
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• 1996

It is very important to predict the future position for the heavy vehicle with evasive maneuvering. In this paper, we considered for the manual image tracking system. The vehicle images are received from gyro stabilized mirror system, pass through the optical lens, processed, and displayed on the TV monitor. The operator try to lay the reticle to the center of vehicle image. When the vehicle is moving, the mirror platform (actually the line of sight) should follow the vehicle and the angular rate information is picked up from the mirror stabilized system. This rate signal should be used to predict the future vehicle position. The problem is that the visual system of the human operator is in the closed loop system. The rate signals are disturbed by the operator. In addition, there are some non linearities concerned with the control handle bar and the servo control system. The proposed Kalman filter, combined with some modifications for operator disturbance rejection, improved the predication of the future vehicle position when compared with the conventional passive filter used.

• Journal of the Korean earth science society
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• v.28 no.1
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• pp.105-111
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• 2007

Seismic and georadar prospecting methods have been used to detect deep seated small tunnel in Korea. The tunnel position interpretation of seismic method has been performed mainly by wave travel time and amplitude. But it was very unstable to interpret the exact tunnel position because of short interval of two measuring boreholes and picking mistake of first arrivals. To solve this problem, this study applied travel-time and amplitude data simulation methods to detect tunnel position.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.187-189
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• 2009

Position estimation in indoor is significant problem, because GPS which is usually used for outdoor positioning cannot be utilized to indoor positioning. Sensor network can be a solution for the positioning. Recently, chirp spread spectrum(CSS) specified in IEEE 802.15.4a provides an ability of ranging. Based on the results of the ranging, a position of a CSS node can be calculated by using trilateration. In this case, Kalman filter can be applied to the trilateration because of the measurement noise. In this paper, we apply the unscented Kalman filter for the trilateration. The trilateration can be represented to a nonlinear state space equation, and the unscented Kalman filter is suitable for nonlinear state space equation. Through the experimental results. we show the accuracy of the estimated position.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.71-79
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• 1997

This paper introduces a methodology of the precise control of a mobile/task robot using visual information captured bythe camera attached at the hand of the task robot. The major problem residing in the precise control of mobile/task robot is providing an accurate and stable base for the task robot through the precise control of mobile robot. On account of uncertainties on the surface, the precise control of mobile robot is not feasible without using external position sensor. In this paper, the methodology for the precise control of mobile robot is proposed, which recognizes the position of mobile robot using the camera attached at the hand of the task robot. While the task robot is approaching to an assembly part, the position of mobile robot is measured using the line correspondence between the image capturesd by the camera and the real assembly part, and using the kinematic transformation from the hand of the task robot to the mobile robot. To verify the solidness of this method, experimental data for the measurement of camera position/orientation and for the precise control of mobile robot using measurement are shown.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.77-83
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• 2003

This paper deals with a position control problem of a hydraulic proportional position control system using a nonlinear friction compensation control. As nonlinear friction, stiction and coulomb friction forces are considered and modeled as deadzone and external disturbance respectively. In order to compensate this nonlinearities, we designed the controller which is the adaptive friction compensator using discrete time Model Reference Adaptive Control method in this paper. Digital Signal Processing board is employed for data acquisition and manipulation. The experimental results show that response is slow and steady-state error cannot be compensated properly without friction compensation but this compensator is effective to obtain fast response and good steady-state response.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.130-135
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• 1998

This paper deals with a position control problem of a hydraulic proportional position control system using a friction compensation control. There are many nonlinearities in hydraulic systems. With only proportional controller, response is slow and steady-state error cannot be compensated properly. Controller designed in this paper achieves fast transient response through the velocity and acceleration feedback and good steady-state response through the friction compensator. A/D and D/A board is employed for data acquisition and manipulation. The experimental results are compared with computer simulation results using Matlab.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.443-447
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• 1996

The meeds of vehicle navigation system are increassing and the accurate determination of position is still of promary improtance. GPS (Global Positioning System)receiver and low cost dead reckoning sensors have been used for vehicle position location. The integartion of these can improve the system performance to cope with accumulating errors and multipath problem in urban area. However, the implementation of integrated system of two sensors is net easy, for their real data ave noises that are not apt to be modeled. This paper discusses how to combine a GPS receiver and dead reckoning sensors. The characteriatics of sensors and their data are investigated, and the system for field test is manufactured. The test results of a selected typical route are presented.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.80-82
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• 1997

A robust position control system for a BLDC motor using new sliding mode control strategy is presented. Using the new variable structure system, reaching phase problem is eliminated and transient response is largely improved by design of nonlinear sliding surface. The design of the sliding mode position controller is robust in motor parameter, load variations and disturbance. Experiment results show that the proposed approach can achieve accurate position motor tracking in face of large parameter variations and external disturbances, such as a robot arm, etc.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.165-170
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• 1997

During the navigation of mobile robot, one of the essential task if to determine the absolute position of mobile robot. In this paper, a method to determine the position of the camera using a vanishing point and neural networks without landmark if proposed. In determining the position of the camera on the world coordinate, there are differences between the real value and the calculated value because of uncertainty in pixels, incorrect camera calibration and lens distortion etc. This paper describes the solution of the above problem using BPNN(Back Propagation Neural Network) and experimental results show the capability to adapt for a mobile robot.