• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.713-718
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• 2003

The CONDENSATION (Conditional Density Propagation) algorithm has a robust tracking performance and suitability for real-time implementation. However, the CONDENSATION tracker has some difficulties with real-time implementation for multiple people tracking since it requires very complicated shape modeling and a large number of samples for precise tracking performance. Further, it shows a poor tracking performance in the case of close or partially occluded people. To overcome these difficulties, we present three improvements: First, we construct effective templates of people´s shapes using the SOM (Self-Organizing Map). Second, we take the discrete HMM (Hidden Markov Modeling) for an accurate dynamical model of the people´s shape transition. Third, we use the competition rule to separate close or partially occluded people effectively. Simulation results shows that the proposed CONDENSATION algorithm can achieve robust and real-time tracking in the image sequences of a crowd of people.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.986-993
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• 2017

Object Tracking is a technique for tracking moving objects over time in a video image. Using object tracking technique, many research are conducted such a detecting dangerous situation and recognizing the movement of nearby objects in a smart car. However, it still remains a challenging task such as occlusion, deformation, background clutter, illumination variation, etc. In this paper, we propose a novel deep visual object tracking method that can be operated in robust to many challenging task. For the robust visual object tracking, we proposed a Convolutional Neural Network(CNN) which shares weight of the convolutional layers. Input of the CNN is a three; first frame object image, object image in a previous frame, and current search frame containing the object movement. Also we propose a method to consider the motion of the object when determining the current search area to search for the location of the object. Extensive experimental results on a authorized resource database showed that the proposed method outperformed than the conventional methods.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.109-114
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• 2004

In this paper, the H$\infty$ control method is applied in the control of SPFC and generators in order to obtain the robust stability performance of the power system. Moreover, a SPFC H$\infty$ controller based on loop shaping is designed to achieve first-rate tracking properties in addition to the robust stability. This robust control method is applied to a Ward and Hale 6-bus power system and the effects are analyzed. The MATLAB program is used for simulation of the robust controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.421-421
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• 2000

In this paper, robust two-degree-of-freedom controller for satellite antenna system which tracks reference signal is designed. Two-degree-of-freedom controller consists of a prefilter and a feedback controller to solve trade-off between robust stability and command response. The feedback controller is designed from specifications like stability, disturbance rejection and robustness via H$_{\infty}$ design technique. In the sequel, H$_2$ optimal prefilter is introduced to improve the command response. This suggests a two-step design, with different types of performance specifications at each stage. In practical problems, this may easily lead to a prefilter of unacceptably high order. In order to avoid high order prefilter we use a particular structure in which both the prefilter and the feedback controller share the same dynamics. H$_2$-prefilter technique proposed in this paper is verified by simulation.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.947-948
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• 2006

This paper proposes a robust posture stabilization control method for wheeled mobile robots. To solve the robust posture stabilization, we introduce reference generation mode, reference tracking mode, and reference regulation mode. In reference generation mode, a kinematic time-invariant controller is used to generate the reference trajectory which starts from the initial posture of the actual robot to the desired posture. In reference tracking mode, a sliding mode position controller is employed in such a way that the actual robot can follow the reference trajectory in the desired forward or backward moving direction, even in the presence of the disturbances in the dynamics. In reference regulation mode, a sliding mode heading direction controller is used such that the actual robot can maintain the desired posture against the disturbances. In this way, robust posture stabilization can be achieved at almost all global regions.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2753-2755
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• 2000

In this paper, the robust position tracking cotroller for a brushless DC motor driving a one-link robot manipulator is proposed. By using the backstepping approach, the adaptive and robust controller is appropriately designed to ensure global stability. The proposed robust backstepping controller can compensate for estimation errors in system parameters in the system with no structural changes in the controller and without destruction of the stability. The closed-loop stability of the system is shown using Lyapunov techniques. The tracking errors are shown to be globally uniformly bounded.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.1-14
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• 2004

This paper surveys some existing direct adaptive feedback control schemes for linear time-invariant systems with actuator failures characterized by the failure pattern that some inputs are stuck at some unknown fixed or varying values at unknown time instants, and applications of those schemes to aircraft flight control system models. Controller structures, plant-model matching conditions, and adaptive laws to update controller parameters are investigated for the following cases for continuous-time systems: state tracking using state feed-back, output tracking using state feedback, and output tracking using output feedback. In addition, a discrete-time output tracking design using output feedback is presented. Robustness of this design with respect to unmodeled dynamics and disturbances is addressed using a modified robust adaptive law.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.411-418
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• 2005

This paper discusses an output-tracking control design method for Takagi-Sugeno fuzzy systems with parametric uncertainties. We first represent the concerned system as a set of uncertain linear systems. The tracking problem is then converted into a stabilization problem thereby leading to a more feasible control design procedure. A sufficient condition for robust practical output tracking is derived in terms of a set of linear matrix inequalities. A numerical example for a flexible-joint robot-arm model has been demonstrated, to convincingly show effectiveness of the proposed system modeling and control design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.175-178
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• 2010

Slow movement of snail can be a benefit since it means less speed of tracking is required to get accurate movement track, but in the other side it is difficult to extract the object because the snail is almost as static as the background. In this paper, we present a technique to track the snail by using one of its common characteristic, dark color of its shell. The technique needs to be robust to illumination change since the experiment is usually to observe the movement of snail both at bright and dim condition. Snail position coordinate in 3D space is calculated using orthogonal stereo vision which combines the information from two images taken from cameras at the top and in front of the aquarium. Experimental results show this technique does not need prior background image extraction and robust to gradual or sudden illumination change.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.26-29
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• 2001

In a target tracking problem the radar glint noise has non-Gaussian heavy-tailed distribution and will seriously affect the target tracking performance. In most nonlinear situations an Extended Robust Kalman Filter(ERKF) can yield acceptable performance as long as the noises are white Gaussian. However, an Extended Robust $H_{\infty}$ Filter (ERHF) can yield acceptable performance when the noises are Laplacian. In this paper, we use the Interacting Multiple Model(IMM) estimator for the problem of target tracking with glint noise. In the IMM method, two filters(ERKF and ERHF) are used in parallel to estimate the state. Computer simulations of a real target tracking shows that hybrid filter used the IMM algorithm has superior performance than a single type filter.