This paper presents a knowledge based system to solve reactive power/voltage control problem in a power system. A need is recognized for new methods to alleviate a bus voltage limit violation more quickly when a power system becomes an emergency state due to contingency. To cope with this object, a set of indices concept which is used to make bus order list of reactive power injection priority is introduced. A set of indices, based on the overall system conditions, consists of steady state stability index, reactive power transmittance indes, voltage severity index and generator fuel cost index. This scheme and empirical rules of the knowledge on the basis of the human expert result in fast decision-making of the reactive power compensation devices since only the amount of devices is determined by the inference in the knowledge based system when the voltage violation is detected. In this approach, control devices such as shunt capacitor (reactor), transformer tap settings and generator voltages are utilized. Also the developed system herein can be used to minimize control action taken or generator fuel cost according to the user's option on the weighting factor. The results of a case study are also presented.

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

In this paper, a design on the superconducting monolith for superconducting pulse magnet is described. Both stability and AC loss parameters are used in the design process, which restricted various design parameters. Determined design parameters satisfy both stability and AC loss restrictions. Finally superconducting monolith is flattened, fitting for magnet and acquiring transposition effect.

In this paper, a new design method for superconducting pulse magnet is presented. Given energy storage capacity, magnet shape parameters are determined to minimize superconducting material quantity. Once the shape parameters are determined, cooling channel is designed and degradation characteristics are confirmed. According to the proposed magnet design concept, relatively uniform and low field distribution is obtained. Therefore, both the quantity of superconducting material and the mechanical load over magnet are reduced.

For the purpose of investigation the thrust force, the lateral force, and the eddy current loss when the primary and the secondary of a single-sided linear induction motor is displaced in the space, this paper proposes an analysis technique for the characteristics of the eddy current induced on the secondary and the magnetic flux density distribution in the y-z plane by F.E.M. To verify the effectiveness of this analysis technique, the starting-thrust force due to a lateral displacement is compared to the experimental data.

A new state feedback control scheme is proposed to improve the stability and dynamic performances of the series resonant converter (SRC). The proposed scheme can be easily implemented without speed limitation. Design parameter of the proposed control is the ratio of the state feedback gains. A closed loop dynamic modeling for the SRC with the proposed control law is derived. Parametric curves which can be used to select the design parameter in the control system are presented. The experimental results show that the excellent dynamic performance of the converter can be obtained by properly selecting the design parameter. The results are further compared with both the theoretical analysis and the frequency control.

This paper presents a Static Var Compensator (SVC) system compensating the reactive power for power system, which consists of a voltage type Pulse Width Modulation (PWM) converter and a reactance linking the converter to the source. The system drives the four quadrant modes. The system determines the magnitude of the input voltage, and then compares it with the magnitude of the source voltage by regulating the phase of the SVC about the source. Therefore, the system generates leading compensation currents when the input voltage is larger than the source in magnitude, and lagging compensation currents for smaller input voltage. Reactive power about voluntary load in power system is smoothly compensated by those compensation currents, and also power factor of source is improved. Furthermore, the SVC system using PWM method may improve the source current waveforms by eliminating the 5th and 7th harmonic components from the input voltages.

In this paper, the convergence and the learning accuracy of the back-propagation (BP) method in neural network are investigated by 1) analyzing the reason for decelerating the convergence of BP method and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative and 2) proposing the modified logistic activation function by defining, the convergence factor based on the analysis. Learning on the output patterns of binary as well as analog forms are tested by the proposed method. In binary output patter, the test results show that the convergence is accelerated and the learning accuracy is improved, and the weights and thresholds are converged so that the stability of neural network can be enhanced. In analog output patter, the results show that with extensive initial transient phenomena the learning error is decreased according to the convergence factor, subsequently the learning accuracy is enhanced.

A singular value approach is presented in order to determine the number of multiple sinusoids from the finite noisy data. Simulations are conducted for Akaike's information criterion (AIC), Rissanen's shortest data description (MDL) and a singular value approach, for various examples with different SNR's and methods of estimating frequencies. And then the performances are compared. Simulation results that the singular value approach is superior to AIC and MDL for FBLP, HOYW and covariance matrix based methods are investigated. The approach with contribute to the frequency estimation of multiple sinusoids from the finite noisy data. Furthermore, this will be applied to the DSPs of communication and bio-medical engineering.

It is hard to keep good quality of coursewares for Computer-Assisted Instruction (CAI), since most CAI coursewares have been developed by programmers rather than by instruction designers. Also, there is no trasplantations among authoring system. This paper describes the design and implementation of an authoring system for CAI to overcome the problems mentioned above. The performance of the system is assured experimentally and then good results are shown compared with other systems.

In this paper, a multi-processor-based supervisory control for automatic assembly system is presented. The proposed supervisory control is organized in terms of C-language and with structured and easily expandable characteristics. Also the controller is designed to possess diagnostic capability including self-diagnosis of processor module. The developed supervisory control has been shown to be very useful via a high speed automatic assembly system with vision capability.