• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.348-351
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• 1993

The simulated annealing(SA) algorithm is a stochastic strategy for search of the ground state and a powerful tool for optimization. based on the anneal ins process used for the crystallization in physical systems. It's main disadvantage is the long convergence time. Therefore, this paper shows that the new algorithm using SA can be applied to reduce the computation time. This idea has been used to solve the estimation problem of the nonlinear parameter.

• The Pure and Applied Mathematics
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• v.30 no.2
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• pp.191-201
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• 2023

In this paper the control system described by Urysohn type integral equation is studied. It is assumed that control functions are integrally constrained. The trajectory of the system is defined as multivariable continuous function which satisfies the system's equation everywhere. It is shown that the set of trajectories is Lipschitz continuous with respect to the parameter which characterizes the bound of the control resource. An upper estimation for the diameter of the set of trajectories is obtained. The robustness of the trajectories with respect to the fast consumption of the remaining control resource is discussed. It is proved that every trajectory can be approximated by the trajectory obtained by full consumption of the control resource.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.284-290
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• 2012

This paper addresses a new passive target tracking problem using the range differences measured by cooperative UAVs. In order to solve the range difference based passive target tracking problem within the framework of linear robust state estimation, the uncertain linear measurement model which contains the stochastic parameter uncertainty is derived by using the noisy range difference measurements. To cope with the performance degradation due to the stochastic parameter uncertainty, the recently developed non-conservative robust Kalman filtering technique [1] is applied. For the cruciform formation flying UAVs, the relationship between the target tracking performance and the measurement errors is quantitatively analyzed. The proposed filter has practical advantages over the classical nonlinear filters because, for its recursive linear structure, it can provide satisfactory convergence properties and is suitable for real-time multiple UAVs applications. Through the simulations, the usefulness of the proposed method is demonstrated.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.63-72
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• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.387-390
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• 2005

Parameter estimation for the probability model of wavelet coefficients is essential to the wavelet-domain interpolation. However, phase uncertainty, one well-known drawback of the orthogonal wavelet transforms, make it difficult to estimate parameters. In this paper, we exploit a phase shifting matrix in order to improve the accuracy of estimation. Nonlinear modeling to capture the interscale characteristics is also described. The experimental results show that the proposed method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.34-40
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• 2005

In this paper, we describe the modeling for the 3D robot laser scanning system consisting of a laser stripe projector, camera, and 5-DOF robot and propose its calibration method. Nonlinear radial distortion in the camera model is considered for improving the calibration accuracy. The 3D range data is calculated using the optical triangulation principle which uses the geometrical relationship between the camera and the laser stripe plane. For optimal estimation of the system model parameters, real-coded genetic algorithm is applied in the calibration process. Experimental results show that the constructed system is able to measure the 3D position within about 1mm error. The proposed scheme could be applied to the kinematically dissimilar robot system without losing the generality and has a potential for recognition for the unknown environment.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.51-60
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• 2007

This paper describes a visual tracking control law of an Unmanned Aerial Vehicle(UAV) for monitoring of structures and maintenance of bridges. It presents a control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position to define a desired trajectory in an unknown 3D environment. The proposed method uses the homography matrix computed from the visual information and derives, using backstepping techniques, an adaptive nonlinear tracking control law allowing the effective tracking and depth estimation. The depth represents the desired distance separating the camera from the target.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.777-782
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• 2011

Neural network technique is widely employed in the fields of signal processing, control systems, pattern recognition, etc. Learning of neural networks is an important procedure to accomplish dynamic system modeling. This paper presents a novel learning approach for differential neural network models based on the Kalman-Bucy filter theory. We construct an augmented state vector including original neural state and parameter vectors and derive a state estimation rule avoiding gradient function terms which involve to the conventional neural learning methods such as a back-propagation approach. We carry out numerical simulation to evaluate the proposed learning approach in nonlinear system modeling. By comparing to the well-known back-propagation approach and Kalman-Bucy filtering, its superiority is additionally proved under stochastic system environments.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.17-29
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• 2007

The major purpose of this article is the comparison of estimation method with Newton-Raphson, Kalman-filter, and prediction method with Kalman prediction. Conditional expectation in space time bilinear(STBL) model, which is a very powerful and parsimonious nonlinear time-series model for the space time series data can be viewed as a set of time series collected simultaneously at a number of spatial locations and time points, and which have appeared in a important applications areas: geography, geology, natural resources, ecology, epidemiology, etc.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.69-75
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• 2009

In this paper, a self-tuning regulator for a speed control of a permanent magnet type stepping motor is proposed. The self-tuning theory provides a nonlinear modeling of a stepping motor drive system and can provide the controller with information regarding the reference variation and parameter variation of the stepping motor through the on-line estimation. The proposed self-tuning regulator organize the positive feedback loop and IP(Integral-Proportional) type. Therefore, the proposed self-tuning regulator has a robust control capabilities during dynamic operation. The availability of the proposed controller is verified through experimental results.