Explicit Solution for a Class of Discrete‐Time Algebraic Riccati Equations

In the present paper we obtain an explicit closed‐form solution for the discrete‐time algebraic Riccati equation (DTARE) with vanishing state weight, whenever the unstable eigenvalues are distinct. We discuss links to current algorithmic solutions and observe that the AREs in such a class solve on one hand the infimal signal‐to‐noise ratio (SNR) problem, whilst on the other hand, in their dual form they solve a Kalman filter problem. We then extend the main result to an example case of the optimal linear quadratic regulator gain. We relax some of the assumptions behind the main result and conclude with possible future directions for the present work.     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

Quantized H∞ Control for Networked Systems with Communication Constraints

The problem of quantized H_∞ control for networked control systems (NCSs) subject to time‐varying delay and multiple packet dropouts is investigated in this paper. Both the control input and the measurement output signals are quantized before being transmitted and the quantized errors are described as sector bound uncertainties. The measurement channel and the control channel packet dropouts are considered simultaneously, and the stochastic variables satisfying Bernoulli random binary distribution are utilized to model the random multiple packet dropouts. Sufficient conditions for the existence of an observer‐based controller are established to ensure the exponential mean‐square stablility of the closed‐loop system and achieve the optimal H_∞ disturbance attenuation level. By using a globally convergent algorithm involving convex optimization, the nonconvex feasibility can be solved successfully. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed method.     

基于利用回归分析法预报上下游相关洪峰水位

根据实际工作需要,为克服采用传统手段利用上下游洪峰水位相关图法来进行洪水预报所带来的不精确性和任意性,笔者利用数学函数方程和回归分析计算软件,使用excel的图形功能,先绘制样本数据散点图,然后在图上添加趋势线,确定了回归方程类型。根据回归方程类型进行了方程系数率定分析,最终推求出预报黑龙江乌云站洪峰水位和洪峰传播时间的数学回归方程,经实例拟合验证,方程计算结果通过检验,基本满足实际应用要求。     

赣江外洲站近50年水沙变化规律

基于赣江外洲站年径流量时间序列(1957-2008年)和年输沙量时间序列(1966-2008年),采用肯德尔秩次相关检验法、有序聚类分析和秩和检验法、小波分析法对赣江水沙变化规律进行分析.结果表明:年径流量时间序列趋势变化不明显,不存在显著跳跃点,当时间尺度为17时,存在以10～12a为周期的丰枯变化.年输沙量时间序列下降趋势明显,在1984年和1998年附近发生跳跃,周期性变化可分为两段,1966-1986年间,在时间尺度为6时平均变化周期约为4a,1986年后,在时间尺度为1时平均变化周期约为3.7a.水土保持、人工采砂、万安水库拦沙等是影响赣江输沙量显著变化的主要因素.     

分布式光纤测温系统的研制

阐述了基于拉曼背向散射和光时域反射（OTDR）技术的分布式光纤测温系统的原理。系统由测温主机、测温光纤和温度解调软件组成,具有灵敏度高、可靠性好、可准确测出光纤沿线温度及信息量大的特点。试验数据表明,系统测温精度高、定位准确,在电力和其他行业得到一定应用,具有工程有效性。     

山区坡体建筑抗震性能研究

以山区坡体上的建筑为研究对象,利用动力时程分析法,输入3条实测地震波和1条人工合成地震波,研究坡体建筑同水平地面建筑动力响应规律的区别和联系。计算结果表明,由于坡体土体对结构的延缓作用而使得坡体建筑动力响应没有水平地面建筑强烈,但由于坡体建筑中桩既抗滑又承重,内力比水平地面建筑要大。研究成果有助于边坡体建筑的抗震设计。     

白山发电厂时钟统一对时系统建设

时间同步系统作为智能化水电厂基础支撑系统,在智能化水电厂建设中发挥着基础服务作用。主要介绍了白山发电厂建设对时系统的结构及主要特点,首次采用PTP授时作为备用信号输入,增加了整个时钟系统的稳定性,提高了系统的授时精度,实现远程异地授时。     

运河水文站流量自动监测系统建立与实现技术

常规流量测验大多采用水文缆道、船测作业模式,现场测验周期长、劳动强度大,不能实现实时、连续、自动监测目标,为此引入德国超声波时差法测流设备。在对运河水文站测验河段分析选择的基础上,从水平、垂直2个方向分析确定时差法设备安装位置,从工程角度对测验平台进行设计,对系统进行同步测验率定,测流精度较高,说明应用时差法流速仪建设流量自动监测系统是可行的。     

小波方法在水资源趋势分析中的能力检验

通过Monte-Carlo模拟试验对小波多分辨分析法在水文时间序列趋势分析中的趋势识别能力进行了研究。结果表明,小波多分辨分析方法的趋势识别能力与时间序列成份组成有关,与序列的噪音分布类型无关,而分析中的分解尺度对于随机性影响大的序列,其值与变差系数成正相关。小波多分辨分析所具有的时频局部化特征,能够合理地反映出时间序列在时间域中的变化特点,其在频域中分析趋势比线性回归和多项式拟合等在时间域中分析趋势的方法更具有优势。另外,在趋势分析前应分析序列中合理的突变成分以及剔除序列中的周期性成分,否则小波趋势分析结果将不可靠。