• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.296-304
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• 2002

A position tracking control schemes on the precise mechanical system in presence of nonlinear dynamic friction is proposed. A nonlinear dynamic friction is regarded as the bristle friction model to compensate effects of friction. The conventional sliding mode controller often has been used as a non-model-based friction controller, but it has a poor tracking performance in high-precision position tracking application since it completely cannot compensate the friction effect below a certain precision level. Thus to improve the precise position tracking performance, we propose the sliding mode control method combined with the friction-model-based observer having tunable structure of the transient response. Then this control scheme has a good transient response as well as the high precise tracking performance compared with the conventional sliding mode control without observer and the control system with similar type of observer. The experiments on the bali-screw drive table with the nonlinear dynamic friction show the feasibility of the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.2
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• pp.48-56
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• 2001

This paper presents the position tracking control of a closed-loop cylinder system using electro-rheological (ER) valve actuators. After manufacturing three sets of cylindrical ER valves on the basis of Bingham model of ER fluid, a 3 dof(degree-freedom) closed-loop cylinder system having the heave, roll and pitch motions is constructed. The governing equations of motion are derived using Lagrange's equation and a control model is formulated by considering nonlinear characteristics of the system, Sliding mode controllers are the designed for these ER valve actuators in order to achieve position tracking control. The effectiveness of trajectory tracking control performance of the proposed cylinder system is demonstrated through computer simulation and experimental implementation of the sliding mode controller.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.165-173
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• 2000

This Paper presents the position tracking control of a closed-loop cylinder system using electro-rheological(ER) valve actuators. After manufacturing three sets of cylindrical ER valves on the basis of Bingham model of ER fluid, a 3 dof(degree-of-freedom) closed-loop cylinder system having the heave, roll and pitch motions is constructed. The governing equations of motion are derived using Lagrange's equation and a control model is formulated by considering nonlinear characteristics of the system. Sliding mode controllers are then designed fer these ER valve actuators in order to achieve position tracking control. The effectiveness of trajectory tracking control performance of the proposed cylinder system is demonstrated through computer simulation and experimental implementation of the sliding mode controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.380-384
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• 1996

This paper represents an adaptive position controller with the disturbance observer for multi-axis servo system. The overall control system consists of three parts : the position controller, the disturbance observer with free parameters and cross-coupled controller which enhances contouring performance by reducing errors. Using two-degrees-of freedom conception, we design the command input response and the closed loop characteristics independently. The servo system can improve the closed loop characteristics without affecting the command input response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer. Moreover, the cross-coupled controller enhances tracking performance. Thus total position control performance is improved. Finally, the performance of the proposed controller shows that it improves the contouring performance along with the reference trajectory in the XY-table.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.434-434
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• 2000

It is the main problem to measure the position and orientation of a robot end effector for the calibration of robots. The calibration methods can be used as a tool to improve the accuracy of robots without change of the arm or control architecture of robots. But such calibration methods require the accurate measurements. Dynamic measurement of position and orientation Provides a solution of this problem and improves dynamic accuracy by dynamic calibration o( robots. This paper describes the development o( the laser tracking system capable of determining the static and dynamic performance of industrial robots. The structure and system components are presented and basic experimental results are included to demonstrate the instrument performance. The system can be applied to the remote controlled mobile robots as weil as the calibration of robots.

• International Journal of Advanced Culture Technology
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• v.4 no.4
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• pp.81-86
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• 2016

In this paper, we propose a simple and effective vision-based tracking controller design for autonomous object tracking using multicopter. The multicopter based automatic tracking system usually unstable when the object moved so the tracking process can't define the object position location exactly that means when the object moves, the system can't track object suddenly along to the direction of objects movement. The system will always looking for the object from the first point or its home position. In this paper, PID control used to improve the stability of tracking system, so that the result object tracking became more stable than before, it can be seen from error of tracking. A computer vision and control strategy is applied to detect a diverse set of moving objects on Raspberry Pi based platform and Software defined PID controller design to control Yaw, Throttle, Pitch of the multicopter in real time. Finally based series of experiment results and concluded that the PID control make the tracking system become more stable in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.930-935
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Combining an LQR method and a proportional control forms a simple PD control. Since LQR control gains are set for the velocity control of the helicopter, a position tracking error occurs. To minimize a position tracking error, neural network is introduced. Specially, in the frame of the reference compensation technique for teaming neural network compensator, a position tracking error of an autonomous helicopter can be compensated by neural network installed in the remotely located ground station. Considering time delay between an auto-helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network performs better than that of LQR itself.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.561-567
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• 2006

This paper deals with a fuzzy controller using IA(Immune Algorithm) for Trajectory Tracking of 2-DOF WMR(Wheeled Mobile Robot). The global inputs to the WMR are reference position and reference velocity, which are time variables. The global output of WMR is a current position. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities on the track of trajectory is necessary. Therefore, a FIAC(Fuzzy-IA controller) is proposed to give velocity compensation in this system. Input variables of fuzzy part are position errors in every sampling time. The output values of fuzzy part are compensation velocities. IA are implemented to adjust the scaling factor of fuzzy part. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.

• Journal of Power System Engineering
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• v.10 no.3
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• pp.97-103
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• 2006

In this study, a position trajectory tracking control algorithm is proposed for a pneumatic artificial muscle driving apparatus composed of a actuator which imitates the muscle of human, a position sensor and a control valve. The controller applied to the driving apparatus is composed of a state feedback controller and disturbance observer. The feedback controller which feeds back position, velocity and acceleration is derived from the linear model of pneumatic artificial muscle driving apparatus. The disturbance observer is designed to improve trajectory tracking performance and to reduce the effect of model discrepancy. The effectiveness of the designed controller is proved by experiments and the experimental results show that the pneumatic artificial muscle driving apparatus with the proposed control algorithm tracks given position reference inputs accurately.