基于粒子群算法进行参数自我调整的广义预测控制算法在汽包液位控制中的应用

PID控制算法的学习性能及泛化性能取决于参数设置;在常规方法中,这些参数以固定值形式参与运算,而当面对复杂分布的数据集时,可能无法挑选出一组能够胜任各种分布情况的参数;因此,提出一种基于粒子群算法(particle swarm optimization, PSO)进行参数自我调整的广义预测控制算法(generalized predictive control, GPC);该算法根据工业锅炉现场环境的复杂性,机组参数的时变性,有效地解决了PID控制的控制精度受到限制的问题;着重讲述了汽包液位控制方案的设计,可看出PSO-GPC控制在汽包液位控制中的重要应用,其次,通过粒子群算法对参数进行辨识,并给出了仿真算例,参数辨识准确,最后用PID控制算法在液位控制中的仿真曲线与广义预测控制算法对锅炉汽包液位进行了仿真曲线进行了对比分析,可见广义预测控制增强了系统的快速性,稳定性好且抗干扰性强。     

B,P掺杂β-Si3N4的电子结构和光学性质研究

运用第一性原理方法, 计算了B, P两种元素单掺杂和共掺杂的β -Si₃N₄材料的电子结构和光学性质. 结果表明: B掺杂体系的稳定性更高, 而P掺杂体系的离子性更强; 单掺和共掺杂均窄化带隙, 且共掺在禁带中引入深能级, 使局域态增强; 单掺杂体系介电函数虚部、吸收谱和能量损失谱各峰均发生红移、幅值减小, 而共掺后介电函数虚部主峰出现蓝移、能量损失峰展宽、高能区电子跃迁大大增强, 且控制共掺杂的B, P比例可获得较低的带电缺陷浓度.     

不同退火方式对Ni/SiC接触界面性质的影响

采用快速热退火(rapid thermal annealing, RTA)法和脉冲激光辐照退火(laser spark annealing, LSA)法, 在n型4H-SiC的Si面制备出Ni电极欧姆接触. 经传输线法测得RTA样品与LSA样品的比接触电阻分别为5.2×10^-4 Ω·cm², 1.8× 10^-4 Ω·cm². 使用扫描电子显微镜、原子力显微镜、透射电子显微镜、拉曼光谱等表征手段, 比较了两种退火方式对电极表面形貌、电极/衬底截面形貌和元素成分分布、SiC衬底近表层碳团簇微结构的影响. 结果表明, 相比于RTA, LSA法制备出的欧姆接触在电极表面形貌、界面形貌、电极层组分均匀性等方面都具有明显优势, 有望使LSA成为一种非常有潜力的制备欧姆接触的退火处理方法.     

On generalized hamiltonian systems

1. PreliminaryIt is well known that{1] a 8ymPlectic form is invariant along the trajectory of a Hamilto-nian system. Based on this fundamental property, certain techniques have been developed.The purpose of this paper is to extend such an approach to a wider class of dynamic systeIns,namely, genera1ized Hamiltonian systems. Our purpose is to investigate a class of dynaInicsystems, which possess a certain "geometric structure".Deflnition 1.1[1'2]. Let M be a tIlallifo1d. w E fl'(M) is call…     

计算电磁学及其在复杂电磁环境数值模拟中的应用和发展趋势

概述计算电磁学的发展历程及其数值方法,并从学术研究、商业软件以及专用软件三个层次论述国内外研究的最新进展.结合复杂电磁环境的应用介绍复杂电磁环境数值模拟平台的研究现状,最后提出未来发展趋势的几点设想.     

Solving the Generalized Machine Assignment Problem in Group Technology

Many existing solution methodologies for machine assignment problems in group technology do not consider factors such as part demand, operation sequence and cost of intercellular moves. We formulate a 0-1 quadratic programming model that takes into account these factors in machine assignment. Two approaches are proposed to solve this problem. The first is an A*-based approach that generates optimal solutions. The second is a heuristic approach developed to solve problems with large number of machines and/or parts. The heuristic approach is shown to be efficient in producing good solutions in a computational study.     

UPWIND SPLITTING SCHEME FOR CONVECTION-DIFFUSION EQUATIONS

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An Overview of Infrared Spectroscopy Based on Continuous Wavelet Transform Combined with Machine Learning Algorithms: Application to Chinese Medicines,Plant Classification,and Cancer Diagnosis

Abstract

Infrared spectroscopy has been a workhorse technique for materials analysis and can result in positively identifying many different types of material. In recent years there have been reports using wavelet analysis and machine learning algorithms to extract features of Fourier transform infrared spectrometry (FTIR). The machine learning algorithms contain back-propagation neural network (BPNN), radial basis function neural network (RBFNN), and support vector machine (SVM). This article reviews the important advances in FTIR analysis employing a continuous wavelet transform (CWT) and machine learning algorithms, especially in the applications of the method for Chinese medicine identification, plant classification, and cancer diagnosis.     

A necessary condition for the minimum of a quadratic form under rearrangements

A necessary condition is derived for a quadratic form p^tGp to be minimal among all permutations of the nonnegative nontrivial vector p. The quadratic form arises from the stability problem of a fixed-fixed taut string loaded with masses at equidistant points.     

Repetition rate multipliers for efficient implementation of multiphoton and pump-probe fluorescence microscopy

With the advances in pulsed laser systems, microscopic imaging techniques such as multiphoton and pump-probe fluorescence microscopy have developed into effective tools for investigating intensity and time-resolved phenomena inside biological systems. However, pulsed lasers used in these techniques usually are commercial systems with repetition frequencies of around 80 MHz. While these systems have proven to be adequate for multiphoton and pump-probe microscopic imaging applications, the temporal separation of the laser pulse train (around 12.5 ns) is long compared to the fluorescence lifetimes of many common fluorescence species. In this work, we present the designs of repetition rate multipliers based on passive optical components that can be used to increase the efficiency in multiphoton and pump-probe fluorescence microscopy. Depending on the lifetime of fluorescence molecules under investigation, the passive repetition rate multiplier can increase the duty cycle of multiphoton or pump-probe microscopy up to fourfold.