• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2188-2195
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• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1865-1874
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• 2011

This paper proposes a novel maximum power point tracking(MPPT) using a new fuzzy control(NFC) algorithm for robust in insolation variation. Maximum power point(MPP) of solar cell has to achieve for improving output efficiency because it is changed with insolation and temperature. Conventional MPPT controller such as constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are researched. But these controller have the problem that is failure to MPP with environment changing. The proposed NFC controller is based the fuzzy control algorithm and able to robust control with environment changing. Also the proposed controller of PV system is modeled by PSIM and the response characteristics according to the parameter variation is compared and analyzed. The validity of this controller is proved through response results.

• Journal of the Semiconductor & Display Technology
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• v.6 no.1 s.18
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• pp.53-57
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• 2007

In this paper, the intelligent estimation algorithm is developed for residual quantity estimate of lithium secondary cell and we suggest the control algorithm to get battery SOC through thermal modeling of electric cell. Lithium secondary cell gives cycle life, charge characteristic, discharge characteristic, temperature characteristic, self-discharge characteristic and the capacity recovery rate etc. Therefore, we make an accurate estimate of the capacity of battery according to thermal modeling to know the capacity of electric cell that is decreased by various special quality of lithium secondary cell. And we show effectiveness through comparison of value as result that use simulation and fuzzy logic.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.154-157
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• 1995

A magnetic levitation control system is nonlinear and very unstable. Thus there should be a stabilizing compensation network and a feedback path. Due to the levitation control a noncontact photoresistor sensor is generally used. One photocell provides a certain amount of variation in length by the ball shadow casted on the cell surface. Furthermore at the boundary of the cell, the linearity of sensitivity deteriorates severely. To overcome the constraints of the length and linearity, an efficient sensor array is deviced and applied in the feedback path of a large-gap magnetic levitation control system. A number of CdS photocells and a summing circuit of the sensor output signals are used for a sensor array. The levitation length of a ball and the transient performances are main objectives of the large-gap suspension system using the sensor array.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.45-53
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• 2015

A I-V and P-V characteristic of solar cell is changed to nonlinear by radiation and temperature. Therefore, to use efficiently PV system, operating point of PV system is must operate at maximum power point always. A performance of conventional the PO and the IC method is depend on the step size. So it has weakness which is must select optimal step size. Also, MPPT control applying PI and fuzzy control is not expected satisfactory performance, because of PI controller has fixed gain and fuzzy control has cumulative error by an integral calculus. Therefore, this paper proposes the VS-PO(Variable Stepsize - Perturbation & Observation) MPPT control that is automatically adjusted the step size according to the operating conditions. The VS-PO MPPT method proposed in this paper analyzes control characteristic about condition of radiation and compares with conventional methods. The validity of this paper proves using this results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1864-1871
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• 2012

This paper proposes the hybrid proportional integral(HBPI) controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.683-691
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• 2000

In this paper, we proposed the cell multiplexer using Hopfield neural network and the bandwidth predictor using the backpropagation neural network in order to make an accurate call setup decision. The cell multiplexer controls heterogeneous traffic and the bandwidth predictor estimates minimum bandwidth which satisfies traffic's QoS and maximizes throughput in network. Also, a novel connection admission controller decides on connection setup using the predicted bandwidth from bandwidth predictor and available bandwidth in networks. And then, we proposed a fuzzy traffic policer, when traffic sources violate the contract, takes an appropriate action and aim proved traffic shaper, which controls burstness which is one of key characteristics in multimedia traffic. We simulated the proposed controller. Simulation results show that the proposed controller outperforms existing controller.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.147-150
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• 2004

Maximum power point tracking for PV systems traditionally uses either perturbation and observation method or incremental conductance method. Both methods require modulation of the output voltage and this leads to significant power loss. In this paper, a method, which senses output circuit voltage and short circuit current and use the above two parameters for optimum control with a fuzzy controller, is introduced. The short circuit current of PV cell represents illumination, and the output circuit voltage carry on information about the temperature. PCS(power conditioning system) is controlled not only feed to inverter for stability voltage variation despite of variety external environment, but also operate in order to feeding voltage and current at maximum power point by boost type chopper.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.468-468
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• 2000

In our laboratory, the control aspects are investigated in the photovoltaic power generation systems (PV systems). The PV system is very good for earth environment, but if it connects to power network system, many problems are raised (protection, voltage, harmonics etc.). In this paper, we present the result of the basic studies for the building of the PV system that amplifies the electric energy obtained from the solar cell. We consider electronic circuits in order to protect the PV system from power surge induced by lightning and also design an electronic circuit in order to detect defaults in the power network system. We would like to integrate these circuits into the PV system by considering its control equipment build by 8-bit microcomputer using various control theory (fuzzy, neural network etc.).

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.93-104
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• 1997

The major economic health problem of dairy cattle is mastitis which can affect 10 to 50% of cow-quarters. This health problem is difficult for many dairy farmers and health advisors to understand, diagnose and control. Without special laboratory testing, most mastitis is overlooked. Estimates of annual mastitis cast per cow vary from $50 to $200. For the nearly 9 million cows in the United States, annual loss to the dairy industry amounts to over one billion. A knowledge-based decision aid has been developed to evaluate mastitis data retrieved electronically from two of nine U. S. regional dairy records processing centers. Heuristic rules to diagnose herd mastitis problems were collected and incorporated into the system from various domain experts. This system information. It allows users to select mastitis control schemes with various degrees of aggressiveness and teaches commonly accepted mastitis control practices.