Robust H∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with modedependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.     

Performance comparison of distributed state estimation algorithms for power systems

A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori (MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.     

Advance selling in the presence of product diffusion effect

Product diffusion refers to the phenomenon that the later demand is dependent on the early sales. To investigate how a firm’s advance selling strategy is affected by the effect of product diffusion, we consider a monopolist seller who sells a fashionable product in a market that comprises of myopic and strategic consumers over two periods (i.e., the advance selling season and the regular selling season). For a linear product diffusion effect we find that, when the effect of product diffusion is positive, the seller may set an extremely high advance selling price to induce the strategic consumers to purchase in the regular selling season, which is counter-intuitive. Moreover, the optimal procurement quantity for the seller may increase in the negative effect of product diffusion and decrease in the amount of strategic consumers. When we extend our model to consider a concave quadratic product diffusion effect, however, the optimal procurement quantity is concave in the amount of strategic consumers. Numerical studies are further presented to discuss the managerial insights.     

变点理论在极值分布阈值选取中的应用

极值理论已经被广泛应用于解决金融、保险等领域的厚尾分布问题，而阚值的选取一直是极值理论实际应用的难点和重点。在已有研究成果基础上。本文尝试引入变点理论进行定量化的阈值选取。分析了变，最理论进行阚值选取的基本原理和方法，利用Burr分布产生的随机样本进行模拟，得到了较好的效果。并在此基础上运用S＆P500和Danish火灾保险数据进行了实证分析。     

NECESSARY AND SUFFICIENT CONDITION FOR GLOBAL CONTROLLABILITY OF A CLASS OF AFFINE NONLINEAR SYSTEMS

In this paper, we investigate the global controllability of a class of n-dimensional affine nonlinear systems with n- 1 controls and constant control matrix. A necessary and sufficient condition for its global controllability has been obtained by using the methods recently developed. Furthermore, we generalize the above result to a class of affine nonlinear systems with a block-triangular-like structure. Finally, we will give three examples to show the applications of our results.     

天津LNG码头SBAS-InSAR时序形变及地面监测数据响应分析

为了查明油气重大基础设施中,由星载雷达干涉测量、地面GNSS形变监测、地下位移传感器监测和管道应力应变监测网络构成的星地一体化监测技术的有效性,本文采用SBAS-InSAR技术提取了天津LNG（Liquefied Natural Gas ）码头区域油气管线区域的长时间序列的地表形变数据,进一步分析了地面GNSS（全球导航定位系统）地表位移、多层深度位移计、管道应变传感器数据与同步的SBAS-InSAR地表形变量的数据响应关系,并进一步分析了雨-旱循环的时序变化规律。结果表明：2019年5月-2022年4月的3年间天津LNG码头区域非均匀沉降最为显著,最高达到-394mm;SBAS-InSAR的时序形变数据15-53mm的沉降形变,在GNSS中有9-57mm的地表位移响应,两者相关显著,具有良好的一致性;SBAS-InSAR地表形变变化特征与多层位移计在1m、2m和3m深的位移数据响应特征都与降水量关系密切,呈现显著的雨季-旱季波动特征,二者具有良好的同步性,说明SBAS-InSAR地表形变变化特征能够揭示地下土层的位移变化特征;SBAS-InSAR地表沉降量与地下管道应变呈正相关, SBAS-InSAR获取的地表形变是反映地下管线应变的良好指标。由星载雷达干涉测量、地面GNSS形变监测、地下位移传感器监测和管道应力应变监测网络构成的星地一体化监测数据的集成应用,能够为未来星地一体化的管道安全监测技术体系构建提供有益的借鉴。     

能量存储:基于全新原理的“纳米弹簧”

许多机械装置如钟表、玩具等都采用弹簧来驱动,其能量的存储与释放是通过弹簧内部原子间距的变化来实现的。但是这种原子间距的变化(即弹性变形)所能存储的体能量密度相对很低,如何提高能量的转换效率以及材料存储的能量密度是当前材料科学理论和实验研究共同关注的一个问题。本研究利用金属钨单晶纳米线在加载时独特的孪晶变形行为,提出了一个可以在纳米尺度下高效存储与释放机械能的新原理,并据此设计了相应的纳米装置——纳米弹簧。与块体弹簧不同,本文提出的纳米弹簧通过表面原子的重构来实现能量的存储与释放。进一步的计算还表明,由于金属钨孪晶界面的移动阻力非常小,金属钨纳米弹簧的能量转换效率可以达到98%;同时该纳米弹簧存储的体能量密度可以超过钟表发条的1600倍,并具有30%的应变以及3GPa的驱动应力。     

介观尺度金属孪晶变形的强烈晶体尺寸效应

主导许多材料力学行为的孪晶变形是一种局部晶体高度协调一致的非弹性剪切变形过程,其发生原因与时空特性仍然保持着某种神秘色彩。本项研究利用纳米压入仪下微柱体压缩与相应的透射电镜原位定量变形表征技术,发现随所用钛铝合金单晶外观尺度逐步减小到1个μm时,孪晶切变所需应力随之显著提高,表现出很强的尺度依赖性。当晶体的外部几何尺度进一步减小到亚μm量级时,材料的塑性变形方式发生了根本性的转变,孪晶变形完全由通常的位错滑移变形取代,而材料所能承受的最大流变应力亦呈现出一种接近于所用材料理想强度水平的＂应力饱和＂平台现象。本研究提出了以螺位错为媒介的孪晶变形＂受激滑移＂模型,完美地解释了孪晶变形具有强烈晶体尺寸效应的内在原因。     

新型掺铒硼铋锶酸盐玻璃的J-O参数计算

用高温熔融法制备了成分为：B2O3-Bi2O3-SrO的新型掺铒硼铋锶酸盐玻璃．测试了样品的发射光谱和吸收光谱．利用Judd—Ofelt理论计算了该玻璃样品的J-O参数（Ω2,Ω4,Ω6）和Er^3＋各相关能级的理论振子强度、实验振子强度等发光参数,并对其发光特性进行了研究．计算结果表明：该硼铋锶酸盐玻璃的共价性强于已被报道的大多数玻璃,且其跃迁几率最大的两个能级为^4I13/2和^4I15／2能级．     

普通公路车速分布特性的回归分析

采用多元线性回归的方法,分别建立了平均车速、15％位车速、85％位车速与车道数、限速值、车道位置、车型、道路饱和度、大型车比例等6个因素之间的回归模型.然后,采用Logistic回归的方法,建立了车速选择的回归模型.分析结果表明:对于双向六车道普通公路,依据15％位车速,对超车道进行最低车速限制;依据85％位车速,对最高车速实施可变限速、分车道限速和分车型限速.外侧车道上的大型车在饱和度较高的情况下,容易选择低速行驶;双向两车道或四车道公路上的小型车在饱和度较低的情况下,容易选择高速行驶.根据车辆选择高速行驶的概率,设置不同的限速设施.利用这2个回归模型可以计算出特定道路条件下的15％位车速、85％位车速以及车辆选择高速行驶和低速行驶的概率,为普通公路在限速及限速设施选择方面提供依据.