Geographically distributed real-time digital simulations using linear prediction

Real-time (RT) simulator is a powerful tool for analyzing operational and control algorithms in electric power systems engineering. For understanding the dynamic and transient behavior of a power systems, significant RT computation capabilities are essential. A single unit of RT simulator has limited simulation capabilities. The most common way of augmenting simulation capability is using a bank of locally connected RT simulators. However, creating a large-sized bank of RT simulators involves significant financial investments and hence may not be feasible at all research facilities. Power and energy systems research facilities that use RT simulators are at diverse physical locations. In addition to RT simulators, research facilities around the world house an array of facilities with unique power, energy, and control systems for innovative research. To leverage these unique research facilities, geographically distributed RT simulation based on Wide Area Network (WAN) is required. Typical RT simulators perform simulations with time-steps in the order of milliseconds to microseconds, whereas data latency for communication on WAN may be as high as a few hundred milliseconds. Such communication latency between RT simulators may lead to inaccuracies and instabilities in geographically distributed RT simulations. In this paper, the effect of communication latency on geographically distributed RT simulation is discussed and analyzed. In order to reduce the effect of the communication latency, a Real-Time Predictor (RTP), based on linear curve fitting is developed and integrated into the distributed RT simulation environment. Two geographically distributed digital RT simulators are used to perform dynamic simulations of an electric power system with a fixed communication latency and the predictor. Empirical results demonstrate the effects of communication latency on the simulation and the performance of the RTP to improve the accuracy of simulations.     

Distributed Control Strategy with Smith's Predictor in a Pilot-Scale Diabatic Distillation Unit

Intrinsic characteristics of distillation such as dead time and high nonlinearities do not allow the complete elimination of transient times when any external disturbance or set-point change occurs. Thus, aiming at the use of easy-tuning systems, a distributed-action control in trays of a diabatic distillation unit with Smith's predictor was implemented in the Simulink environment to further reduce transient times and out-of-specification product. The distributed-action strategy with Smith's predictor led to a reduction of 33.3 min (33 %) in the transient time of the top temperature control loop and 66 % in out-of-specification product, when compared with the conventional strategy, and thus is shown to be an efficient approach to increasing the productivity of distillation plants.     

Mixed convective peristaltic flow of Eyring‐Prandtl fluid with chemical reaction and variable electrical conductivity in a tapered asymmetric channel

The influence of inconstant electrical conductivity and chemical reaction on the peristaltic motion of non‐Newtonian Eyring‐Prandtl fluid inside a tapered asymmetric channel is investigated. The system is concerned by a uniform external magnetic field. The heat and mass transfer are considered. The problem is controlled mathematically by a system of nonlinear partial differential equations which describe the velocity, temperature, and nanoparticle concentration of the fluid. By means of long wavelength and low Reynolds numbers, our system is simplified. It is explained by using the multi‐step differential transform method as a semi‐analytical technique. The distributions of velocity, temperature, nanoparticle concentration, as well as pressure gradient and pressure rise are obtained as a function of the physical parameters of the problem. The effects of these parameters on these distributions are deliberated numerically and illustrated graphically through a set of figures. The results indicate that the parameters play a significant role in controlling the velocity, temperature, nanoparticle concentration, pressure gradient, and pressure rise.     

A second-order Mehrotra-type predictor-corrector algorithm with a new wide neighbourhood for semi-definite programming

In this paper, we present a new second-order Mehrotra-type predictor–corrector algorithm for semi-definite programming (SDP). The proposed algorithm is based on a new wide neighbourhood. We are particularly concerned with an important inequality. Based on the inequality, the convergence is shown for a specific class of search directions. In particular, the complexity bound is O(√nlog?^?1) for the Nesterov–Todd search direction and O(n log?^?1) for the Helmberg-Kojima-Monteiro search direction. The derived complexity bounds coincide with the currently best known theoretical complexity bounds obtained so far for SDP. We provide some preliminary numerical results as well.     

轧机AGC系统的Smith预估补偿

轧机厚度控制系统中厚度误差反馈信号的纯滞后影响了系统的稳定及响应速度。本文介绍了采用Smith预估器进行预估补偿的方法来克服纯滞后的影响,改善系统的动态特性。     

Preparation of sharp-melting hard palm midfraction and its use as hard butter in chocolate

Preparation of hard palm midfractions (PMF) and its use as a cocoa butter equivalent ingredient were studied. Hard PMF is obtained by multistep fractionation of palm oil involving dry fractionation (DF) and/or solvent fractionation (SF), usually using hexane or acetone. From our experience, in acetone, a polar solvent, symmetrical 1,3-disaturated triacylglycerols tend to selectively crystallize more than nonsymmetrical 1,2- or 2,3-disaturated triacylglycerols, making it suitable for obtaining the solid midfraction. Unfortunately, triacylglycerols are very soluble in hexane, and temperatures at least 15 degrees lower than those required for acetone must be used for equivalent crystal yields. On the other hand, DF is a less expensive and safer process. Thus, multistep fractionation combining DF and SF using acetone was developed to achieve sufficient removal of high-melting components, and further enrichment of 1,3-dipalmitoyl-2-oleoylglycerol and the hard PMF was obtained by triple-step fractionation of palm olein or double-step fractionation of soft PMF. Compared to conventional hard PMF, this hard PMF had a steeper melting curve and better snapping and sharp-melting qualities when used in chocolate. Heat resistance of the hard PMF chocolate was similar to the conventional hard PMF chocolate, and its bloom resistance could be improved by adding polyglycerol fatty acid esters.     

Predicting potential deadlocks in multithreaded programs

In a multithreaded program, competition of threads for shared resources raises the deadlock possibility, which narrows the system liveness. Because such errors appear in specific schedules of concurrent executions of threads, runtime verification of threads behavior is a significant concern. In this study, we extended our previous approach for prediction of runtime behavior of threads may lead to an impasse. Such a prediction is of importance because of the nondeterministic manner of competing threads. The prediction process tries to forecast future behavior of threads based on their observed behavior. To this end, we map observed behavior of threads into time‐series data sets and use statistical and artificial intelligence methods for forecasting subsequent members of the sets as future behavior of the threads. The deadlock prediction is carried out based on probing the allocation graph obtained from actual and predicted allocation of resources to threads. In our approach, we use an artificial neural network (ANN) because ANNs enjoy the applicable performance and flexibility in predicting complex behavior. Using three case studies, we contrasted results of the current and our previous approaches to demonstrate results. Copyright © 2015 John Wiley & Sons, Ltd.     

不稳定串级时滞过程的改进型内模控制

针对不稳定串级时滞过程,提出了改进型内模控制(IMC)方法。控制系统副回路采用改进的内反馈控制结构,能够有效去除副控制器对主回路的影响,从而简化主控制器的设计。主回路采用改进的内模控制结构,在反馈通道增加干扰抑制控制器,使主电路的跟踪特性和干扰抑制特性实现解耦,通过对控制器进行设计,能有效地抑制被控过程参数的变化和干扰对系统性能的影响。     

基于改进型Smith预估器的同步施工网络控制系统

根据同步施工网络控制系统的控制原理,分析了时变、随机和不确定的网络时延对同步误差控制所产生的影响。针对传统Smith预估器用于多被控对象同步控制时存在的缺陷与不足进行了分析,提出了一种改进型Smith预估器,实现了对网络时延、被控对象纯滞后因子以及同步误差控制器的多重Smith预估补偿,将其从内部反馈回路中彻底消除,预估模型无需预估与在线测量其大小与变化规律。通过基于控制器局域网络(controller area network,简称CAN)的盾构管片拼装机同步网络控制系统,对常规比例积分微分(proportion integral derivative,简称PID)同步网络控制和基于改进型Smith预估器的PID同步网络控制性能进行了仿真对比分析,并通过实验进行了验证。结果表明,常规PID网络控制同步误差为-3～3mm,基于改进型Smith预估器的PID网络控制同步误差为-1.5～1.5mm,后者可显著提高同步施工网络控制系统的同步控制性能与精度。     

Applied Nonparametric Statistical Methods

In the analysis of spatial data, it is common to predict a spatial exceedance and its associated exceedance region. This is scientifically important, because unusual events tend to strongly affect the environment. We use classes of loss functions based on image metrics (e.g., Baddeley's loss function) to predict the spatial-exceedance region. We then propose a joint loss to predict a spatial quantile and its exceedance region. The optimal predictor is obtained by minimizing the posterior expected loss given the process parameters, which we achieve by simulated annealing. Various predictors are compared through simulation. This methodology is applied to a spatial data set of temperature change over the Americas.