• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.1-40
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• 2001

In this paper, control theoretic approaches are proposed to guarantee QoS (Quality of Series) such as packet delay and packet loss of real-time traffic in high-speed communication network. Characteristics of variable rate real-time traÆc in communication networks are described. The mathematical model describing networks including source and destination nodes are suggested. By a traffic control mechanism, it is shown that worst-case end-to-end transfer delay of traffic can be controlled and packet loss can be prevented. The simulation shows results of delay control and buer level control to raise QoS in realtime traffic.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.577-582
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• 1989

This is a study of the translational end-point control of a single link flexible arm-with a tip mass. The beam is mounted on a translational mechanism driven by the ball screw, whose rotation is controlled by DC servomotor. The problem of shifting the end-point from its initial position to the commanded position is studied analytically both for the open-loop control subjected to some path functions and for the closed-loop control using the feedback of the tip information.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.417-424
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• 2003

In this paper, we introduce and analyze a feedback control model of TCP/AQM dynamics. Then, we propose the Pro-active Queue Management (PAQM) mechanism, which can provide proactive congestion avoidance and control using an adaptive congestion indicator and a control function for wide range of traffic environments. The PAQM stabilizes the queue length around a desired level while giving smooth and low packet loss rates independent of the traffic load level under a wide range of traffic environment. The PAQM outperforms other AQM algorithms such as Random Early Detection (RED) [1] and PI-controller [2]

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.364-367
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• 1995

In this paper, a design method of learning flight control system via input matching is proposed. The proposed learning control system is a simple structure which has an artificial neural network and feedback mechanism, and it is a useful method to control nonlinear systems.

• Journal of KSNVE
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• v.9 no.6
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• pp.1240-1246
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• 1999

A prior error estimator which is solving structural dynamic problems and which is based on the generalized-method, is developed. Since the proposed error estimator is computed with only previous information, the time step size can be adaptively selected without the feedback mechanism. This paper shows that the automatic time stepping algorithm using the error estimator performs an efficient time integration. To verify its efficiency, several examples are numerically investigated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04a
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• pp.213-217
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• 1993

This paper presents an end-point of 1-link flexible robot arm with a tip-mass by using self-turning fuzzy algorithm. The arm is mounted on a translational mechanism driven by a ballscrew, whose rotation is controlled by CD servomotor. Tip position is controlled so that it follows a desired position. A feedback signal is composed of both the tip-displacement error and change in error. This paper gives the experimental tip responses according to the variations of tip-mass and beam-length, and also showes the effects of reducing the residual vibrations occuring at the end-point.

• Proceedings of the IEEK Conference
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• summer
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• pp.189-192
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• 2004

This paper focuses on a TCP window-based flow control mechanism with Explicit Congestion Notification (ECN). We investigate the fundamental problem of achieving a fair window control for TCP, which cooperates with ECN. This is done by using feedback congestion pricing as a means of estimating the state of bottleneck router. The problem is solved by achieving network optimal performance, which maximize the total user utilities. We then look at the simulation of such scheme.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.994-997
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• 2003

This Paper presents a study of the performance of a DC servo motor with a model reference adaptive fuzzy speed controller (MRAFSC) in the presences of load disturbances. MRAFSC comprised inner feedback loop consisting of the fuzzy logic controller (FLC) and plant, and outer loop consisting of an adaptation mechanism which is designed for tuning a control rule of the FLC. Experimental results show the good performance in the DC servo motor system with the proposed adaptive fuzzy controller.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.501-507
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• 2004

The uniquely large dimensions of Giant radio galaxies (GRGs) make it possible to probe for stringent limits on total energy content, Faraday rotation, Alfven speeds, particle transport and radiation loss times. All of these quantities are more stringently limited or specified for GRG's than in more 'normal' FRII radio sources. I discuss how both global and detailed analyses of GRG's lead to constraints on the CR electron acceleration mechanisms in GRG's and by extension in all FRII radio sources. The properties of GRG's appear to rule out large scale Fermi-type shock acceleration. The plasma parameters in these systems set up conditions that are favorable for magnetic reconnection, or some other very efficient process of conversion of magnetic to particle energy. We conclude that whatever mechanism operates in GRG's is probably the primary extragalactic CR acceleration mechanism in the Universe.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.149-152
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• 2000

In the Internet, multimedia data transfer is hard to guarantee the characteristics of the Real-Time because of the Best-Effort of the nature of IP, then additional mechanism is applied to multimedia application for real-time data. In this paper, we introduce the nature of multimedia and the necessary facility for real-time protocol. We propose protocol layer, which has necessary function above mentioned and offer the end-to-end transfer far real-time data. Also, the proposed protocol perform a next low operation: 1) a required information for QoS control by using Feedback mechanism is obtained from sender, 2) divided a transferred packet by delay and loss priority. 3) recognized the low service models, and 4) decided a bandwidth and QoS according to a network state