This paper shows that a well-defined energy function can be developed to reflect the transfer conductances for multi-machine power systems under an assumption that all transmission lines have uniform R/X rations. The energy function is derived by introducing a pure reactive equivalent system for the given system. In this study, a static energy function reflecting transfer conductances is also derived as well as the transient energy function. The proposed static energy function is applied to voltage stability analysis and tested for various sample systems. The test results show that the accuracy of voltage stability analysis can be considerable improved by reflecting transfer conductances into the energy function.

This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management program. Bass diffusion model was applied in this paper, which has different values according to the following parameters; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameters precisely, there has been no empirical way in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints can be empirical results or expert's decision. Case studies show the diffusion curves and forecasted values of the peak for the high-efficient lighting. The feedback and nonlinear least-square parameter estimation methods used in this paper enable us to evaluate the status and to predict the effect of DSM program.

The management of power factor(PF) in the distribution line is treated according to the measurement a month about the feeder unit at the substation. In Korea, we have not researched into power factor in distribution system due to it's less weight. The reactive power in advanced countries is controlled automatically by the compensative condenser switch on/off under the monitoring. This paper first presents the optimal condenser position and proper capacity by lagrangue factor ${\lambda}_{Q}$ which is the line loss index about reactive power unit. Therefore, the largest ${\lambda}_{Q}$ node is the condenser injection point and we find out the best condenser capacity when the line loss is saturated by the moderation of condenser volume. By this method, we suggest 0.6% uprising PF by injection of 15 kVA condenser. Additionally, PF is analysed into 5 areas; large city, middle city, small city, farm village, fishing village by the use of Power Platform which is classified the same concept of the low load management in KEPCO. Two feeders of each area are selected by the worst results of PF in specified areas.

This study is focused on the reliability evaluation for distribution system based on deterministic evaluation technique. Average failure rates, average outage time, and average annual outage time of electrical parts and load points are calculated through network reduction method and failure mode & effective analysis method. And reliability indices of distribution system are calculated. Finally, by employing analytic hierarchy process method, unique index which evaluates and improves the distribution system is calculated. As a result, finding weak points and expansion schedule of the system is possible. The usefulness of this method is verified by applying it to the Inchon International Airport.

Many papers have recently been presented to develop energy functions for power systems. However, earlier studies adopted case-by-case approaches, which failed to give a general approach to deal with various kinds of generator models. In this paper, two useful theorems are developed regarding the integral relationships of the generator power versus its phasor current and voltage. By using the proposed theorems, an exact energy conservation law can be derived from the complex integral. The proposed energy conservation law, which is free of the generator model, can be utilized to develop energy functions for various kinds of generator models including the speed governors and exciters. An illustrative example is given for a multimachine system with the Eq' model of generator. This thesis also shows a possibility of more accurate and fast stability analysis by using the proposed Energy Conservation Law.

A high speed digital distance relaying algorithm based on a Wavelet Transformation is proposed. To obtain stable phasor values very quickly, first, a lowpass filter which has low cutoff frequency is used. Secondly, db2(Daubechies 2) Wavelet which has the data window of 4 samples is used. A FIR filter which removes the DC-offset component in current relaying signals is applied. In accordance with a series of tests, the operation time of the relaying algorithm is less than 3/4 cycles after faults in a 80 [km], 154[kV], 60[Hz] over-head transmission line system.

This paper presents the framework for analysis of small-signal stability. In this framework the equilibrium points of system DAE model are traced using continuation method and instability points are determined on the solution path. Especially Implicit shift QR-modified Arnoldi method is utilized to calculated the rightmost eigenvalues. Small-signal stability is becoming one of the major factors that affect the ATC in the environment of deregulation. Stability limited ATC is easily evaluated in this stability analysis process.

This paper presents an approach for the optimal heating load Identification using Diagonal Recurrent Neural Networks(DRNN). In this paper, the DRNN captures the dynamic nature of a system and since it is not fully connected, training is much faster than a fully connected recurrent neural network. The architecture of DRNN is a modified model of the fully connected recurrent neural network with one hidden layer. The hidden layer is comprised of self-recurrent neurons, each feeding its output only into itself. In this study, A dynamic backpropagation (DBP) with delta-bar-delta learning method is used to train an optimal heating load identifier. Delta-bar-delta learning method is an empirical method to adapt the learning rate gradually during the training period in order to improve accuracy in a short time. The simulation results based on experimental data show that the proposed model is superior to the other methods in most cases, in regard of not only learning speed but also identification accuracy.

This paper presents a new algorithm to construct the modular network model for SSR analysis by simply applying KCL to each node and KVL to all branches connected to the node sequentially. This method has advantages that the model can be derived directly from the system data for transient stability study and turbine/generator shaft model, the resulted model in the form of augmented state matrix is very sparse, and thus efficient SSR study of a large scale system becomes possible. The proposed algorithm is verified with the IEEE First and Second Benchmark models.

This paper presents an algorithm for evaluating power wheeling effects. For a specific operating condition, the effects are quantified by the sensitivity of specific quantities of interest with respect to power wheeling level. Quantities of interest are total operating cost, transmission losses, and system security which is quantified with several indices. The model and solution method are applied on a example power system and the results are presented.

The water level control of a steam generator in the unclear power plant is an important process. Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolutions to solve it. In this paper, it is suggested that the established simple PID controller in low power has the ability to remove disturbances and trace the set-point, and then possesses the real-time self-tuning function according to the variety of moving peculiarity of a plant. This function realized by making use of fuzzy logic. PID parameters are formulated by a variable ${\alpha}$ and made it fluctuate by a fuzzy inference according to level error and level error change. This mechanism makes application of actual plant effective as well as taking advantage of improving the efficiency of water level controller by way of adding the function of self-tuning instead of replacing PID controller. The computer simulation of this scheme shows the improved performance compare to conventional PID controller.

In this paper, a method to guarantee system continuity is developed, which can be applied to discontinuity problem in the time domain of restructurable control system. This method can be summarized as input alternation using weight change considering convergence speed of system mode. Input is changed from 'system continuity guarantee input,' which is defined as a input that minimizes the change of state variables, to 'alternative controller input,' which is selected by Neil's PI/EAM[3]. AIDC aircraft model is used for simulation. By showing the waveform of system input and state variable, we can sure that this method is effective for depression of system shock like jerk.

In this paper, an efficient method of analysis and design of fault detection filter is presented. Since the directional constraint is applied to the eigenstructure associated with the detection space, an eigenvector is determined by the eigenvalues associated with other eigenvectors. Further, the assignment of a pair of eigenvalue and eigenvector leads to the fixation of overall eigenstructure related with the detection space. Using the transmission zeros and the transmission zero vectors, these phenomenon are clearly proven, and an efficient algorithm for design of the fault detection filters is presented.

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

In conventional GPS/DR integration schemes, the GPS position (or pseudo-range) information is used in calibrating DR sensors. In those schemes, however, an inaccurate calibration may degrade the position accuracy when the GPS measurement is not available. This paper presents a new integration scheme where the GPS velocity information is used in calibrating DR sensors. Also proposed is a new error model of DR sensors for calibrating the bias error and the tilt error in dynamic environments. The proposed model makes it possible that the errors of both the DR sensor parameters and the velocity are calibrated using the GPS carrier-based velocity(or the pseudo-range rate) measurement while the DR position error is calibrated using the GPS position measurement. Since the DR sensors are calibrated accurately, the positioning accuracy is drastically improved when the GPS measurements are unavailable.

In large-scale systems, we frequently encounter the time-delay and the uncertainty, and these should be considered in the design of controller because these are the source of the degradation of the system performance and instability of system. In this paper, we consider the robust stability of the linear large scale systems with the uncertainties and the time-delays. The considered uncertainties are both structured uncertainty and the unstructured uncertainty. Also, the considered time-delays are time-varying having finite time derivative limits. Based on the Lyapunov theorem and the linear matrix inequality(LMI) technique, we present two sufficient conditions that guarantee the robust stability of the system. The conditions are expressed as the LMI forms which can be easily checked their feasibility by using the well-known LMI control toolbox. Finally, we show by two examples that our results are less conservative than the previous results.

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

In this paper, the Timed Petri-Nets(TPN) modeling of Modular Cell Manufacturing Systems(MCMS) was investigated to overcome the limit of batch mode operation, which has been one of the most popular manufacturing types to produce an extensive industrial output and to be able to adopt to suitable and quickly changing manufacturing environments. A model of the MCMS was developed in reference to the actual TFT-LCD manufacturing system. TFT-LCD manufacturing system is not mass-productive in batch mode, but it operates in the form of MCMS which consists of a sequence of several cells with four processes of operation, including those of color filter(C/F), TFT, cell, and module. The cell process is further regrouped in those of Front-End and Back-End. For the Back-End cell process, it is reconstructed into a virtual model, consisting of three cells. The TPN modeling encompasses those properties, such as states and operations of machines, the number of buffers, and the processing time. The performance of the modeling was further examined in terms of scheduling system. The productivity in each cells was examined with respect to the change of failure rate of the cell machines and Automatic Guided Vehicles(AGV) using simulation by TPN.

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-AS1 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilize the disturbance observer loop by saturating the differential changes of the image features.

As the integration ratio and operation speed increase, it has become an important problem to estimate the dissipated power during the design procedure as a method to reduce the TTM(time to market). This paper proposed a prediction model to estimate the maximum dissipated power of a CMOS logic gate. This model uses a calculational method. It was formed by including the characteristics of MOSFETs of which a CMOS gate consists, the operational characteristics of the gate, and the characteristics of the input signals. As the modeling process, a maximum power estimation model for CMOS inverter was formed first, and then a conversion model to convert a multiple input CMOS gate into a corresponding CMOS inverter was proposed. Finally, the power model for inverter was applied to the converted result so that the model could be applied to a general CMOS gate. For experiment, several CMOS gates were designed in layout level by $0.6{\mu}m$ layout design rule. The result by comparing the calculated results with those from HSPICE simulations for the gates showed that the gate conversion model has within 5% of the relative error rate to the SPICE and the maximum power estimation model has within 10% of the relative error rate. Thus, the proposed models have sufficient accuracies. Also in calculation time, the proposed models was more than 30 times faster than SPICE simulation. Consequently, it can be said that the proposed model could be used efficiently to estimate the maximum dissipated power of a CMOS logic gate during the design procedure.

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

This paper presents concrete pattern recognition method to identify the strength of concrete by evidence accumulation with multiple parameters based on artificial intelligence techniques. At first, zero-crossing(ZCR), mean frequency(MEANF), median frequency(MEDF) and autoregressive model coefficient(ARC) are extracted as feature parameters from ultrasonic signal of concrete. Pattern recognition is carried out through the evidence accumulation procedure using distance measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern recognition.

This paper proposes concurrent event propagation technique for timing analysis. The technique makes it possible to find several input vectors and sensitizable paths at the same time. The concurrent event propagation technique is based on the event driven simulation and the timing analysis technique with boolean equations. The technique propagates as many events as possible at the same time while preventing propagation of boolean terms which do not sensitize paths. Since events do not propagate through false paths, the longest path which successfully propagates events to one of the primary outputs is one of the longest sensitizable paths. The technique can speed up timing analysis by unifying path sensitization and maximum delay calculation.

A power distribution facility map is drawn on cadastral map. Besides, grid lines are added on the map for sectionalization. For automatic recognition of the map, we first extract recognizing regions. In this paper, we propose an extraction method of recognizing regions by partially extending thinned image. The proposed method is consist of three phases, binarization phase, thinning phase and partial extending phase. The first phase generate a binary image using threshold value which is obtained by histogram analysis. The binary image contains many part of recognizing regions, but not all. The second phase generate thinned image which is generated by appling thinning operator to the binary image. And the third phase extends thinned image from terminal point until satisfying termination condition. The proposed method is tested on several power distribution facility maps, and the results are presented.

In this paper, a new method for controlling the pointing device using EOG(electrooculogram) signal generated from eye movement was suggested. The basic idea of the method is to control the direction of pointer, as using the results of measuring each component of the horizontal EOG and the vertical EOG by angle of eye-gaze. As a practical example, pointing device controlling the personal computer's pointer is manufactured. The designed pointing device consists of pre-amplifier, A/D converter, serial transmission device and PC program. That is, first, the EOG is amplified by pre-amplifier. Secondly, the amplified EOG is digitized and transmitted to personal computer by PIC16C74A. Finally, the software for controlling the pointer on personal computer is programed. As the result, the measured horizontal EOG and vertical EOG by eye-gaze angle had high linearity; the correlation coefficients of the regression line were 0.998 and 0.996 respectively. And the developed pointing device is able to control the personal computer's pointer, and the average of the errors between the objective value and the observed value had 3.77% for horizontal axis and 5.85% for vertical axis. The pointing device developed in this study is able to control personal computer's pointer by subject's eye movement, that is, the user's intention. Furthermore, the algorithm of this study is applicable for many field, such as a new method remote control, a new wheelchair control and so forth.