• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.77-89
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• 2009

Visual tracking technique is one of the essential things which are very important in the major fields of modern society. While contour tracking is especially necessary technique in the aspect of its fast performance with target's external contour information, it sometimes fails to track target motion because it is affected by the surrounding edges around target and weak egdes on the target boundary. To overcome these weak points, in this research it is suggested that PDMs can be obtained by generating the virtual 6-DOF motions of the mobile robot with a CCD camera and the image tracking system which is robust to the local minima around the target can be configured by constructing Active Shape Model in modular base. To show the effectiveness of the proposed method, the experiment is performed on the image stream obtained by a real mobile robot and the better performance is confirmed by comparing the experimental results with the ones of other major tracking techniques.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.3
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• pp.97-105
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• 1997

The aim of this paper is to introduce a design technique of the Two-Degree-of-Freedom(TDF) satellite-tracking control system which has not only the robust stability for a unstructured uncertainty but also the robust performance for a structured uncertainty. This TDF system which can design the feedforward controller KI and the feedback one K independently is designed by , $\mu$-synthesis. The effectiveness of this TDF system is verified and compared with the One-Degree-of -Freedom(ODF) satellitetracking control system by computer simulation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.589-597
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• 2011

In this paper, optimal tuning of a cross-coupled controller linked with the feedforward controller and the disturbance observer is studied to improve contouring and tracking accuracy as well as robustness against disturbance. Previously developed integrated design and optimal tuning methods are applied for developing the robust tuning method. Strict mathematical modeling of the multivariable system is formulated as a state-space equation. Identification processes of the servomechanism are conducted for mechanical servo models. An optimal tuning problem to minimize both the contour error and settling time is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servo control system. Constraints such as relative stability, robust stability and overshoot, etc. are considered for the optimization. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm the control performance and robustness despite the variation of parameters of the mechanical subsystems.

• Journal of Power Electronics
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• v.4 no.1
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• pp.28-38
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• 2004

In this paper, the position control of a detuned indirect field oriented control (IFOC) induction motor drive is studied. A proposed Simple-Neuro-Controllers (SNCs) are designed and analyzed to achieve high-dynamic performance both in the position command tracking and load regulation characteristics for robotic applications. The proposed SNCs are trained on-line based on the back propagation algorithm with a modified error function. Four SNCs are developed for position, speed and ｄ-ｑ axes stator currents respectively. Also, a synchronous proportional plus integral-derivative (PI-D) two-degree-of-freedom (2DOF) position controller and PI-D speed controller are designed for an ideal IFOC induction motor drive with the desired dynamic response. The performance of the proposed SNCs and synchronous PI-D 2DOF position controllers for detuned field oriented induction motor servo drive is investigated. Simulation results show that the proposed SNCs controllers provide high-performance dynamic characteristics which are robust with regard to motor parameter variations and external load disturbance. Furthermore, comparing the SNC position controller with the synchronous PI-D 2DOF position controller demonstrates the superiority of the proposed SNCs controllers due to attain a robust control performance for IFOC induction motor servo drive system.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1094-1102
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• 2008

Through the motion control experiment using Industrial Emulator(Model 220 by ECP), the performance comparison of three kinds of controllers such as PID, RIC and LQR was carried out. It was shown that RIC has the best performance in the presence of disturbances such as step one, sinusoidal one and Coulomb friction for the rigid body. LQR using feedback state variables has the best tracking performance far the flexible body. The performance of PID controller is low compared to other controllers, but the design process is simple. The most advanced controller is LQR. In order to attenuate disturbance, an additional state observer should be used to estimate it, making more complex control system. RIC lies between PID and LQR in view of complexity of design. Even though RIC is not complicated, it has good disturbance rejection ability and less tracking error. By considering these aspects, the RIC is suggested as high precision controller to be used in motion control system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.107-116
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• 2015

In compliance with digital device growth, the proliferation of high-tech computers, the availability of high quality and inexpensive video cameras, the demands for automated video analysis is increasing, especially in field of intelligent monitor system, video compression and robot vision. That is why object tracking of computer vision comes into the spotlight. Tracking is the process of locating a moving object over time using a camera. The consideration of object's scale, rotation and shape deformation is the most important thing in robust object tracking. In this paper, we propose a robust object tracking scheme using Random Forest. Specifically, an object detection scheme based on region covariance and ZNCC(zeros mean normalized cross correlation) is adopted for estimating accurate object location. Next, the detected region will be divided into five regions for random forest-based learning. The five regions are verified by random forest. The verified regions are put into the model pool. Finally, the input model is updated for the object location correction when the region does not contain the object. The experiments shows that the proposed method produces better accurate performance with respect to object location than the existing methods.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.10
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• pp.871-880
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• 2000

A twin-servo mechanism is used to increase the payload capacity and assembling speed of high precision motion control systems such as semiconductor chip mounters. In this paper, we focus on the modeling of the twin-servo system and propose its network representation. And also, we propose a robust synchronizing motion control algorithm to cancel out the skew motion of the twin-servo system caused by different dynamic characteristics of two driving systems and the vibration generated by high accelerating and decelerating motions. The proposed control algorithm consists of separate feedback motion control algorithms for each driving system and a skew motion compensation algorithm. A robust tracking controller based on internal-loop compensation is proposed as a separate motion controller and its disturbance attenuation property is shown. The skew motion compensation algorithm is also designed to maintain the synchronizing motion during high speed operation, and the stability of the whole closed loop system is proved based on passivity theory. Finally, experimental results are shown to illustrate control performance.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.6
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• pp.1141-1149
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• 1992

This paper presents a robust centralized control scheme for a magnetic bearing system which supports a rigid rotor at both shaft ends in the radial direction. The negative stiffness element and the inductive force associated with bearing magnetic field are considered in the dynamic model of the system. For this model, the controllability and observability are examined, and then a robust control theory is applied to design two types of multi-input multi-output servocontrollers. A general servocompensator is embedded in the first one and a centralized PID controller is suggested as a second one. By simulation study, the performance of two types of servocontrollers are compared in the aspects of disturbance rejection, reference tracking and the robustness limit.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.90-102
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• 2009

In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.861-877
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• 2016

This paper first discusses the disadvantages of the existing CamShift Algorithm for real time face tracking, and then proposes a new Camshift Algorithm that performs better than the existing algorithm. The existing CamShift Algorithm shows unstable tracking when tracing similar colors in the background of objects. This drawback of the existing CamShift is resolved by using Kinect’s pixel-by-pixel depth information and the Skin Detection algorithm to extract candidate skin regions based on HSV color space. Additionally, even when the tracking object is not found, or when occlusion occurs, the feature point-based matching algorithm makes it robust to occlusion. By applying the improved CamShift algorithm to face tracking, the proposed real-time face tracking algorithm can be applied to various fields. The results from the experiment prove that the proposed algorithm is superior in tracking performance to that of existing TLD tracking algorithm, and offers faster processing speed. Also, while the proposed algorithm has a slower processing speed than CamShift, it overcomes all the existing shortfalls of the existing CamShift.