Direct analysis of transient stability: Experience with the Taipower system

A direct method for transient stability analysis of a multimachine power system is presented. Emphasis is placed on the detailed development and evaluation of the proposed method in transient stability assessment. An energy-type Lyapunov function, taking into account the effect of transfer conductance, is introduced first. The potential energy boundary surface method is then adopted to determine the critical energy value quickly. The main computational burden in the direct method lies in the reduction of the admittance matrices. In this paper, an efficient reduction technique incorporating the sparsity technique and compensation theory is developed. Finally, the proposed method was tested on the Taipower system, which is the only power system in Taiwan. The results obtained confirm the validity and accuracy of the proposed method, and hence demonstrate the superiority and potential of the direct method in real power system applications.     

Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.     

Comparisons of PWM and one-cycle control for power amplifier with multilevel converter

Based on the concepts of cascade multilevel converters and one-cycle technique, comparisons are conducted to characterize the distortion of the pulsewidth modulation (PWM) and one-cycle control methods that were applied to converters. Simulation results for the different control schemes are obtained in PSIM software initially to see the effect of one-cycle control different from that of PWM control. Through the comparisons, the advantages and disadvantages are identified for each method. The one-cycle scheme is better than PWM control in reducing undesirable harmonics and tracing dynamic waveforms. Simulation and experimental results are also provided to verify the conclusions.     

Effects of hot carrier induced interface state generation insubmicron LDD MOSFET's

A two-dimensional numerical simulation including a new interface state generation model has been developed to study the performance variation of a LDD MOSFET after a dc voltage stress. The spatial distribution of hot carrier induced interface states is calculated with a breaking silicon-hydrogen bond model. Mobility degradation and reduction of conduction charge due to interface traps are considered. A 0.6 μm LDD MOSFET was fabricated. The drain current degradation and the substrate current variation after a stress were characterized to compare the simulation. A reduction of the substrate current at V_g ≃0.5 V_d in a stressed device was observed from both the measurement and the simulation. Our study reveals that the reduction is attributed to a distance between a maximum channel electric field and generated interface states     

Integration of mobile vehicles for automated material handlingusing Profibus and IEEE 802.11 networks

This paper focuses on a method to integrate mobile devices such as a mobile robot, automated guided vehicle, and unmanned container transporter to form an automated material handling system. In this paper, the stationary devices are connected via a Profibus network while the mobile devices are communicating via an IEEE 802.11 wireless LAN. In order to integrate these two networks, a protocol converter is developed on a PC platform that runs two interacting processes with shared internal buffers. The protocol converter performs a role of translator between two different protocols by converting the format of a data frame. In addition to this basic conversion function, the protocol converter has a virtual polling algorithm to reduce the uncertainty involved in accessing the wireless network. Finally, the integrated network. of Profibus and IEEE 802.11 is experimentally evaluated for its data latency and throughput, which shows the feasibility of the Profibus-IEEE 802.11 network for industrial applications involving mobile devices     

Low RF noise and power loss for ion-implanted Si having an improved implantation process

Very-low-transmission line noise of <0.25 dB at 18 GHz and low power loss /spl les/0.6 dB at 110 GHz have been measured on transmission lines fabricated on proton-implanted Si. In contrast, a standard Si substrate gave much higher noise of 2.5 dB and worse power loss of 5 dB. The good RF integrity of proton-implanted Si results from the high isolation impedance to ground, as analyzed by an equivalent circuit model. The proton implantation is also done after forming the transmission lines at a reduced implantation energy of /spl sim/4 MeV. This enables easier process integration into current VLSI technology.     

Modeling Temperature in Coupled Electrical and Thermal Simulations of the Electroconsolidation® Process

Electroconsolidation® is a process for densifying complex-shaped parts by using electrically conductive particulate solids as a pressure-transmitting medium. The part is immersed in a bed of the particulate medium contained in a die chamber. Sintering temperature is achieved by resistive heating of the medium while applying compaction pressure. The process is capable of ultrahigh temperatures and short cycle times and offers the potential for low processing costs.

Control of the process and selection of process conditions require knowledge of the temperatures within the die. Temperature gradients exist because of the high heating rate and because of variations of density and electrical resistivity of the medium due to the presence of the part. Direct measurement of temperature with thermocouples or other conventional means is impractical because of the high temperatures, high currents, and high pressures that are involved. Therefore, a computer model was developed to predict temperature as a function of time and applied voltage for any location in the die. The computer model is composed of three parts: a geometrical model to approximate the density and resistivity variations in the medium, a finite-element model to calculate the rate of resistive heating within each element, and a finite-difference model to calculate the temperature distribution based on solution of the heat-transfer equations. Predicted temperatures have been shown to be in excellent agreement with measurements, and numerical simulation provided encouraging consistency and reasonably accurate predictions of temperature profiles within the die. The model demonstrated the feasibility of a new process to achieve simultaneous application of pressure and heat to powder densification in Electroconsolidation.