• Journal of Power System Engineering
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• v.12 no.6
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• pp.36-41
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• 2008

A crane is very important mechanical systems in industrial applications to move huge objects. Especially, in marine port terminals, it is used to place container boxes at desired position within given operating time. However, such system is faced with environmental disturbance such as wind from the sea, thus crane control system is required to cope with this nature. This paper proposed robust and adaptive control algorithm of a complicated 3D crane against the environmental disturbance. We simplify a mathematical design procedure to derive our control algorithm. We conduct real-time experiment using a crane simulator to evaluate its superiority and reliability.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.69-72
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• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.36-41
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• 1999

Shock wave propagating in the particle suspension has important applications. Examples are shock waves occurring in the solid rocket plume and detonation of dusty particles by shock waves. Experimental and numerical investigations on this subject have drawn much attention. More recently, Sivier et al. numerically simulated the experiment of Sommerfeld using the unstructured adaptive grid. They used the Eulerian-Eulerian approach based on the continuum assumption for both gas and particles. In the present paper, a new numerical method using the Lagrangian particle tracing technique and unstructured particle-adaptive grid for the polydisperse system is presented. It is explained why the existing numerical calculation has showed discrepancy with the experimental results by Sommerfeld.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.337-346
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• 2004

The control scheme using fuzzy modeling and Parallel Distributed Compensation (PDC) concept is proposed to provide asymptotic tracking of a reference signal for the flexible joint manipulators with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop multi-input/multi-output system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1004-1014
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• 2007

In sensor networks, it is crucial to reliably and energy-efficiently deliver sensed information from each source to a sink node. Specifically, in mobile sink (user) applications, due to the sink mobility, a stationary dissemination path may no longer be effective. The path will have to be continuously reconfigured according to the current location of the sink. Moreover, the dynamic optimal path from each source to the sink is required in order to reduce end-to-end delay and additional energy wastage. In this paper, an Adaptive Reversal Optimal path Tree (AROT) protocol is proposed. Information delivery from each source to a mobile sink can be easily achieved along the AROT without additional control overhead, because the AROT proactively performs adaptive sink mobility management. In addition, the dynamic path is optimal in terms of hop counts and the AROT can maintain a robust tree structure by quickly recovering the partitioned tree with minimum packet transmission. Finally, the simulation results demonstrate that the AROT is a considerably energy-efficient and robust protocol.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.696-702
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• 2007

This paper proposes a regional feature preserving adaptive interpolation algorithm for natural images. The algorithm can be used in resolution enhancement, arbitrary rotation and other applications of still images. The basic idea is to first scan the sample image to initialize a 2D array which records the edge direction of all four-pixel squares, and then use the array to adapt the interpolation at a higher resolution based on the edge structures. A hybrid approach of switching between bilinear and triangulation-based interpolation is proposed to reduce the overall computational complexity. The experiments demonstrate our adaptive interpolation and show higher PSNR results of about max 2 dB than other traditional interpolation algorithms.

• Journal of Computing Science and Engineering
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• v.6 no.1
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• pp.26-38
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• 2012

Java has been increasingly used in programming for real-time systems. However, some of Java's features such as automatic memory management and dynamic compilation are harmful to time predictability. If these problems are not solved properly then it can fundamentally limit the usage of Java for real-time systems, especially for hard real-time systems that require very high time predictability. In this paper, we propose to exploit multicore computing in order to reduce the timing unpredictability that is caused by dynamic compilation and adaptive optimization. Our goal is to retain high performance comparable to that of traditional dynamic compilation, while at the same time, obtain better time predictability for Java virtual machine (JVM). We have studied pre-compilation techniques to utilize another core more efficiently, preoptimization on another core (PoAC) scheme to replace the adaptive optimization system (AOS) in Jikes JVM and the counter based optimization (CBO). Our evaluation reveals that the proposed approaches are able to attain high performance while greatly reducing the variation of the execution time for Java applications.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.168-177
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• 2007

In a number of fields, robots are being used for two purposes: efficiency and safety. Most robots, however, have single-actuator mechanism for each joint, where the tasks are performed with high stiffness. High stiffness causes undesired problems to the environment and robots. This study proposes redundant actuator mechanism as an alternative idea to cope with these problems. In this paper, Double-Actuator Unit (DAU) is implemented at each joint for applications of multi-link manipulators. The DAU is composed of two motors: the positioning actuator and the stiffness modulator, which enables independent control of positioning and compliance. A three-link manipulator with DAUs enables adaptive control of RCC. By modulating the joint stiffness of the manipulator and controlling the position of RCC, we can significantly reduce contact force during assembly tasks and surgical procedures.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.739-744
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• 2004

This paper presents an adaptive approach to control the amount of slip of the torque converter bypass clutch using its estimated friction coefficient. The proposed approach can be readily implemented using the inexpensive speed sensors currently installed in an automobile. A measurement feedback control law to drive the slip error to zero together with an adaptation law to identify the unknown friction coefficient is developed using the Lyapunov control design method. The robustness of the control and adaptation laws to parametric and/or torque uncertainties as well as the convergence of the friction coefficient are investigated. Simulation results verify the viability of the proposed control algorithm in real-world vehicle control applications.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.