Model Predictive Control for Discrete‐Time Systems with Random Delay and Randomly Occurring Nonlinearity

In this paper, the model predictive control problem is investigated for a class of discrete‐time systems with random delay and randomly occurring nonlinearity. The randomly occurring nonlinearity, which describes the phenomena of a class of nonlinear disturbances occurring in a random way, is modeled according to a Bernoulli distributed white sequence with a known conditional probability. Moreover, the random delay is governed by a discrete‐time finite‐state Markov chain. The approach of delay fractioning is applied to the controller synthesis. It is shown that the proposed model predictive controller guarantees the stochastic stability of the closed‐loop system. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed method.     

基于互联网的电力设备维修技术的研究

电力设备的诊断与维护在电力系统的运行中起着非常重要的作用。本文着重介绍利用信息、智能控制、网络等技术构建基于互联网的电力设备网络管理系统,为电力设备的诊断与维护提供一个方便的讨论、共享及全球合作的技术平台。     

加强制度建设 加大惩防力度 推动党风廉政建设和反腐败工作深入开展

2010年,水利系统按照省委、省纪委部署,坚持把反腐倡廉建设与推进兴水战略相结合,深入开展了党风廉政建设。通过健全制度、强化监督、深入教育,保证了厅党组重大决策和重要决定的落实,用制度管人管     

一种新型两自由度柔性并联机械手的优化设计

对一种新型高速并联机械手,在弹性动力学层面上以系统的动态性能为优化目标对其截面参数进行优 化设计．首先,利用有限元法建立系统的弹性动力学方程．然后,研究分析了系统第一阶固有频率对截面参数的灵 敏度,以便确定设计变量．最后,分别采用了两套优化设计方案对系统进行优化设计．结果表明这两种方案都能满 足设计要求．     

Limits of Learning-Based Superresolution Algorithms

Learning-based superresolution (SR) is a popular SR technique that uses application dependent priors to infer the missing details in low resolution images (LRIs). However, their performance still deteriorates quickly when the magnification factor is only moderately large. This leads us to an important problem: “Do limits of learning-based SR algorithms exist?” This paper is the first attempt to shed some light on this problem when the SR algorithms are designed for general natural images. We first define an expected risk for the SR algorithms that is based on the root mean squared error between the superresolved images and the ground truth images. Then utilizing the statistics of general natural images, we derive a closed form estimate of the lower bound of the expected risk. The lower bound only involves the covariance matrix and the mean vector of the high resolution images (HRIs) and hence can be computed by sampling real images. We also investigate the sufficient number of samples to guarantee an accurate estimate of the lower bound. By computing the curve of the lower bound w.r.t. the magnification factor, we could estimate the limits of learning-based SR algorithms, at which the lower bound of the expected risk exceeds a relatively large threshold. We perform experiments to validate our theory. And based on our observations we conjecture that the limits may be independent of the size of either the LRIs or the HRIs.     

Segment-based adaptive hyper-Erlang model for long-tailed network traffic approximation

Modeling the long-tailedness property of network traffic with phase-type distributions is a powerful means to facilitate the consequent performance evaluation and queuing based analysis. This paper improves the recently proposed Fixed Hyper-Erlang model (FHE) by introducing an adaptive framework (Adaptive Hyper-Erlang model, AHE) to determine the crucially performance-sensitive model parameters. The adaptive model fits long-tailed traffic data set directly with a mixed Erlang distribution in a new divide-and-conquer manner. Compared with the well-known hyperexponential based models and the Fixed Hyper-Erlang model, the Adaptive Hyper-Erlang model is more flexible and practicable in addition to its accuracy in fitting the tail behavior.

概率引导的随机采样一致性算法

为了提高随机采样一致性算法的计算效率,提出一种概率引导的随机采样一致性算法.根据采样模型在原始数据上的检验结果调整每个样本点的采样概率,使得正确样本和正确模型被采样的概率得到提高.在首次获得正确模型之后,样本采样与模型更新构成了一个正反馈环节,经过若干次迭代后,正确样本被采样的概率远超过错误样本被采样的概率.理论分析和实验数据表明,该算法收敛需要的迭代次数较少,有效地提高了随机采样一致性算法的效率.     

无线传感器网络在环境污染监测中的应用设计

环境污染是可持续经济发展中必须解决的问题,如何采取高效、便捷的方法监测环境显得尤为必要;文中提出了一种基于GPRS网络和Zigbee无线传感器网络的远程环境监控系统;首先简单介绍了Zigbee技术,重点介绍了该系统的监控方案、通信机制、网络节点的硬件设计及其工作原理和系统的软件实现流程;经检验该系统可以实现对环境的远程在线自动监测,具有经济、高效、实时、便捷、节能等特点,对促进环保事业的发展具有重要意义。     

基于eM-Plant的图书退货系统建模与仿真

由于品种多、批量小而总量大,退书处理在我国以人力为主的图书配送中心作业中已经成为重要的问题环节。为此对某省新华书店的退货系统进行了粗分和二次分拣的播种式作业流程设计,并采用eM-Plant仿真软件进行建模,分析了分拣模式、人力配置和作业效率,验证了退书作业方案。     

面向生产线全生命周期的数字孪生模型应用

针对传统生产方式存在的管理成本大,生产效率低的问题,为实现智能化生产,设计了基于数字孪生技术的生产线全生命周期管理应用框架。首先基于物理生产线的多元数据,通过建模技术构建了生产线数字孪生模型,分别从生产线的规划阶段、调试阶段、运行阶段,为物理实体生产线提供仿真预演分析、连通调试、生产状态监控、数据可视化等服务。通过孪生模型对实际生产线的规划到运行阶段进行指导和改进,使企业生产线平衡率提高了6.84%,年产量增加了792件,结果表明该方法有效。