• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2055-2062
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• 1996

This paper presents a method of compensating for the gain and phase imbalance of quadrature modulator and demodulator. The gain and phase imbalance are compensated using the received power after the compensation pattern was transmitted at tranceiver. The proposed method is less vulnerable to changes in the transmission channel than the conventional method because compensation is made possible within the tranceiver system, and even the change in phase mblance in accordance with frequency can be compensated utilizing the adaptive algorithm. According to numerical results, a normalized eye opening and a bit error rate are improved by 1.8dB and 3.8dB, respectively.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.251-262
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• 1999

In the automated manufacturing systems, the problem regarding how to make production activities flexible is even more important and critical than that regarding how to product large quantities, and the more flexible, if possible, the manufacturing system is, the more competitiveness and profitable factors it gets. This research, therefore, concentrated on establishing the flexibility and evaluating performance on the manufacturing system, operational flexibility is considered because of enabling the manufacturing system to get both the improvement of production rate and the adaptive ability of environment changes. For it, we used the analytical tool, GSPNs, which is a kind of timed Petri-Nets. GSPNs is competent enough to consider practical situations just like operation priorities, machine failure, randomness, concurrency and so on. Through the GSPNs analysis, it is confirmed that in the manufacturing system with operational flexibility is compatible with the traditional performances such as production rate or mean waiting time.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1051-1052
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• 2006

This paper deals with mathmatical of an induction motor, considering non-linearity in the torque balance equation under closed loop operation with a reference speed. A controller based on Adaptive Nuro-Fuzzy Inference System (ANFIS) is developed to minimize overshoot and settling time following sudden changes in load torque. The overall system is modeled and simulated using the Matlab/simulink and Fuzzy Logic Toolbox. The advantages of fuzzy logic and neural network based fuzzy logic controller. Required training data the ANFIS controller is generated by simulation of the anti-windup PI controller is eliminated using the ANFIS controller. The transient deviation of the response from the set reference following variation in load torque is found to be negligibly samll along with a desirable reduction in settling time for the ANFIS controller.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.954-957
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• 1997

In this paper, we analyze the voltage sag caused by reclosing on electric power distribution system. When a fault is on the electric system, a reclosing operation brings a voltage sag on the feeders which is supplied with a common substation transformer. By analyzing the fault wave-form measured in the field, it is showed that a voltage sag is in proportion to a fault current. Also, we propose an adaptive reclosing scheme. This scheme changes the number of reclosing as a function of the magnitude of a fault voltage and the fault type. As the proposed scheme is compared with conventional scheme in the side of voltage sag and permanent fault, it is verified that the proposed scheme is more effective than conventional scheme.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.323-330
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• 2014

Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.3
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• pp.33-46
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• 2007

This study deals with the adaptive multiuser OFDM (Orthogonal Frequency Division Multiplexing) system which adjusts the resource allocation according to the environmental changes in such as wireless and quality of service required by users. The resource allocation includes subcarrier assignment to users, modulation method and power used for subcarriers. We first develop a general optimization model which maximizes data throughput while satisfying data rates required by users and total power constraints. Based on the property that this problem has the 0 duality gap, we apply the subgradient dual optimization method which obtains the solution of the dual problem by iteration of simple calculations. Extensive experiments with realistic data have shown that the subgradient dual method is applicable to the real world system, and can be used as a dynamic resource allocation mechanism.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.211-217
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• 2000

A main contribution of this paper is the development of a Hopfield network-based algorithm for the fault diagnosis of the actuators in linear system with uncertainties. An unknown input decoupling approach is introduced to the design of an adaptive observer so that the observer is insensitive to uncertainties. As a result, the output observation error equation does not depend on the effect of uncertainties. Simultaneous energy minimization by the Hopfield network is used to minimize the least mean square of errors of errors of estimates of output variables. The Hopfield network provides an estimate of the gains of the actuators. When the system dynamics changes, identified gains go through a transient period and this period is used to detect faults. The proposed scheme is demonstrated through its application to a simulated second-order system.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.454-457
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• 2000

In this paper, an efficient rate control algorithm based on rate prediction is proposed for maintaining a smooth buffer variation and a small buffer size. The proposed method adjusts the quantization scaling factor by using the predicted bit-rate to meet the target bit budget exactly. Experimental result show that the proposed prediction-based rate control scheme can regulate the bit-rate across scene changes more effectively and achieve better PSNR performance than existing rate control mechanisms such as the MPEG-2 Test Model 5 (TM5) and the Adaptive Scene Analysis (ASA).

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1839-1842
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• 2002

Ad hoc networks are characterized by multi- hop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. In this paper, we proposed a new technique to adjust the zone radius by concentrating the changes of network traffic in a particular direction, which we refer to as AZRP. We demonstrate that even though ZRP and AZRP share a similar hybrid routing behavior, the differences in the protocol mechanics can lead to significant performance differentials. We discuss the algorithm and report on the performance of AZRP scheme, and compare it to the ZRP routing protocol. Our results indicate clearly that AZRP outperforms ZRP by reducing significantly the number of route query messages. And thereby increases the efficiency of the network load.

• 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.