• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.13-13
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• 2000

This paper considers delay-dependent guaranteed cost control for uncertain time-delay systems with norm-bounded parametric uncertainties. A new delay-dependent condition for the existence of the guaranteed cost control law is presented in terms of linear matrix inequalities (LMI). An algorithm involving convex optimization is proposed to design a controller which guarantees the suboptimal minimum of the guaranteed cost of the closed-loop system for all admissible uncertainties.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.87-87
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• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.509-518
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• 2002

This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.897-905
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• 2006

This study considers an experimental design of disturbance compensation control to improve stabilization performance of main battle tanks. An adaptive non-parametric design technique based on the Filtered-x Least Mean Square(FXLMS) algorithm is applied in the consideration of model uncertainties. The optimal compensator is designed by two-step design procedures: determination of frequency response function of the disturbance compensator which can cancel the disturbance of series of single harmonics by using the FXLMS algorithm and determination of the compensator polynomial which can fit the frequency response function obtained in the first step optimally by using a curve fitting technique. The disturbance compensator is applied to a simple experimental gun-torsion bar-motor system which simulates gun driving servo-system. Along with experimental results, the feasibility of the proposed technique is illustrated. Experimental results demonstrate that the proposed control reduces the standard deviation of stabilization error to 47.6% that by feedback control alone. The directional properties of the FXLMS Algorithm such as the direction of convergence and its convergence speed are also verified experimentally.

• Smart Structures and Systems
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• v.4 no.4
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• pp.493-515
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• 2008

Semi-active control systems have attracted a great deal of attention in recent years because these systems can operate on battery power alone, proving advantageous during seismic events when the main power source of the structure may likely fail. The behavior of semi-active devices is often highly non-linear and requires suitable and efficient control algorithm. This paper presents the comparative study and performance of variable semi-active friction dampers by using recently proposed predictive control law with direct output feedback. In this control law, the variable slip force of semi-active variable friction damper is kept slightly lower than the critical friction force, which allows the damper to remain in the slip state during an earthquake, resulting in improved energy dissipation capability. This control algorithm is able to produce a continuous and smooth slip forces for a variable friction damper. The numerical examples include a structure controlled with multiple variable semi-active friction dampers and with multiple passive friction dampers. A parameter, gain multiplier defined as the ratio of damper force to critical damper control force, is investigated under four different real earthquake ground motions, which plays an important role in the present control algorithm of the damper. The numerically evaluated optimum parametric value is considered for the analysis of the structure with dampers. The numerical results of the variable friction dampers show better performance over the passive dampers in reducing the seismic response of structures.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.136-141
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• 2009

This paper proposed a framework for handover method in continuously tracking a person of interest across cooperative pan-tilt-zoom (PTZ) cameras. The algorithm here is based on a robust non-parametric technique for climbing density gradients to find the peak of probability distributions called the mean shift algorithm. Most tracking algorithms use only one cue (such as color). The color features are not always discriminative enough for target localization because illumination or viewpoints tend to change. Moreover the background may be of a color similar to that of the target. In our proposed system, the continuous person tracking across cooperative PTZ cameras by mean shift tracking that using color and shape histogram to be feature distributions. Color and shape distributions of interested person are used to register the target person across cameras. For the first camera, we select interested person for tracking using skin color, cloth color and boundary of body. To handover tracking process between two cameras, the second camera receives color and shape cues of a target person from the first camera and using linear color calibration to help with handover process. Our experimental results demonstrate color and shape feature in mean shift algorithm is capable for continuously and accurately track the target person across cameras.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.56-61
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• 2013

This paper presents a development of the Advanced Emergency Braking (AEB) Algorithm for passenger vehicles. The AEB is the system to slow the vehicle and mitigate the severity of an impact when a rear end collision probability is increased. To mitigate a rear end collision, the AEB comprises of a millimeter wave radar sensor, CCD camera and vehicle parameters of which are processed to judge the likelihood of a collision occurring. The main controller of the AEB algorithm is composed of the two control stage: upper and lower level controller. By using the collected obstacle information, the upper level controller of the main controller decides the control mode based not only on parametric division, but also on physical collision capability. The lower level controller determines warning level and braking level to maintain the longitudinal safety. To decide the braking level, Last Ponit To Brake and Steer (LPTB/LPTS) are compared with current driving statues. To demonstrate the control performance of the proposed AEBS algorithm's, closed-loop simulation of the AEBS was conducted by using the Matlab simlink and CarSim software.

• Journal of the Korea Society of Computer and Information
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• v.20 no.10
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• pp.15-21
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• 2015

In this paper, we propose a stable automatic signature verification algorithm applicable to various smart devices. The proposed algorithm uses real and forgery data all together, which can improve the verification rate dramatically. As a tool for signature acquisition in a smart device, two applications, one using touch with a finger and the other using a pressure-sensing-stylus pen, are developed. The verification core is based on SVM and some modifications are made to include the characteristics of signatures. As shown in experimental results, the minimum error rate was 1.84% in the SVM based method, which can easily defeat 4.38% error rate with the previous parametric approach. Even more, 2.43% error rate was achieved with the features excluding pressure-related features, better than the previous approach including pressure-related features and only about 0.6% more error than the best result, which means that the proposed algorithm can be applied to a smart device with or without pressure-sensing-stylus pens and used for security purposes.

• Journal of Korean Association for Spatial Structures
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• v.21 no.1
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• pp.79-86
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• 2021

Control performance of a smart tuned mass damper (TMD) mainly depends on control algorithms. A lot of control strategies have been proposed for semi-active control devices. Recently, machine learning begins to be applied to development of vibration control algorithm. In this study, a reinforcement learning among machine learning techniques was employed to develop a semi-active control algorithm for a smart TMD. The smart TMD was composed of magnetorheological damper in this study. For this purpose, an 11-story building structure with a smart TMD was selected to construct a reinforcement learning environment. A time history analysis of the example structure subject to earthquake excitation was conducted in the reinforcement learning procedure. Deep Q-network (DQN) among various reinforcement learning algorithms was used to make a learning agent. The command voltage sent to the MR damper is determined by the action produced by the DQN. Parametric studies on hyper-parameters of DQN were performed by numerical simulations. After appropriate training iteration of the DQN model with proper hyper-parameters, the DQN model for control of seismic responses of the example structure with smart TMD was developed. The developed DQN model can effectively control smart TMD to reduce seismic responses of the example structure.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.