时延网络控制系统的稳定性分析

本文分析了一类随机网络控制系统,主要对系统传感器的取样周期区间划分了更小的子区间,针对系统控制器的信号的随机变化,得到了系统渐近稳定的充分条件。     

一种基于优化观测向量的E-HMM的人脸识别方法

在研究伪二维隐马尔可夫模型(E-HMM)的基础上,结合优化观测向量,将离散余弦的优化方法加入到特征提取中,增强了系统对噪声、光照以及姿态的鲁棒性,提高了识别的效率.本文首先对二维人脸图像进行建模分析,然后对模型进行训练,最后利用训练好的隐马尔可夫模型完成人脸识别.实验结果表明,该方法识别率高,鲁棒性好,具有较高的实际应用价值.     

工业控制系统的网络化的应用现状与发展

介绍了工业控制系统网络化发展前景,综述了嵌入式系统在工业控制网络中的应用,OPC DX标准在多种工业以太网中的应用,以及无线局 域网与工业控制网络的结合等工业控制系统网络化进程中的热点问题。     

网络化制造的研究框架与未来主题

采用文献研究方法,总结并提出网络化制造的相关定义及网络化制造系统的基本框架,并对网络化制造的类型和研究现状进行了划分,着重从模式转化、技术创新、社区价值、大数据时代四个方面对网络化制造的未来发展趋势进行了分析和展望,并指出挖掘客户需求将是网络化制造模式升级的关键。     

网络化多种数据通信的通用数据采集装置的研究

在当前信息技术发展的过程中,数据采集技术在其中有着十分重要的作用,它不仅有利于自动化系统的正常使用,还可以有效的对相关数据信息进行采集,从而满足社会经济发展的相关要求。而且随着科学技术的不断进步,人们也将网络化多种数据通信技术应用到了其中,这就使得数据采集装置的性能和自动化程度得到了有效的提升。本文首先通过对网络化数据采集装置的系统设计的内容进行介绍,其次讨论了网络化数据采集装置的应用系统,以供相关人士参考。     

非线性编辑系统的架构与网络化研究

非线性编辑技术是计算机图形图像高度数字化的产物。本文首先提出了非线性编辑系统的相关概念,阐述了非线性编辑的工作原理与特点,最后详细分析了非线性编辑系统的架构与如何实现非线性编辑系统的网络化。     

基于GMM-HMM的话题生命周期状态识别及趋势预测方法

[目的/意义]本研究对正处于演化过程中的话题进行状态识别及趋势预测,为相关部门了解话题现状,对话题进行有效监管提供科学依据。[方法/过程]首先,考虑网民情感,结合话题的新颖度和关注度,构建话题生命周期状态观测指标;其次,基于隐马尔可夫模型(HMM)和高斯混合模型(GMM)的原理,提出话题生命周期状态识别及趋势预测方法;最后,选用微博话题构建数据集,设计对比实验,验证方法的有效性。[结果/结论]基于GMM-HMM的话题状态识别及趋势预测方法的F1值和准确率均高于87%,MAPE低于3.5%,相较于GaussianHMM和BP神经网络具有较大优势。     

非线性系统中随机谐振的研究

在非线性离散时间系统中,一定的噪声有时可能对信号的传输和处理起到促进作用,这种现象称之为随机谐振（Stochastic Resonance简称SR）.利用“Adaptive stochastic resonance”这篇文献中给出的一种新的信噪比（SNR）的定义,并用它来度量一个非线形离散时间系统的SR现象。通过仿真证实了当输入是正弦波,噪声是高斯噪声时,系统的输出信噪比中具有SR现象。最后我们讨论设想将仿真的结果推广到更一般的情况,即当输入周期信号,输入概率密度函数为偶函数且均值为零的噪声时,此系统有可能产生SR现象.     

基于LDA-HMM的知识流动模式发现研究

【目的/意义】知识流动模式能够动态反映知识形态在知识流动中发生的变化，体现学科系统中不同知识体 系的发展规律，因此从科学文献角度出发研究知识流动模式的发现具有重要意义。【方法/过程】以图书情报学领域 为例，设计一种组合方法，首先采用LDA（latent Dirichlet allocation，隐狄里克雷分布）主题模型进行领域内文献的主 题聚类，然后提取引用和被引用数据构成主题知识流入、流出特征，并作为HMM（Hidden Markov Model，隐马尔可 夫模型）训练模型的观测值序列，识别不同的隐藏状态，进一步对模型的拟合效果进行评估，最后通过聚类分析将 隐藏状态序列与知识流动模式一一对应，揭示图书情报学领域存在不同知识流动模式的差异性。【结果/结论】实验 结果显示，不同类型的知识流动模式具有不同的表现形式，反映了领域内部主题研究的演变历程，为理解和认识科 学发展趋势具有一定价值。     

具有随机掉包特性的网络控制系统研究现状与展望

从系统建模、控制策略与调度、网络时延、数据丢包和系统稳定性等角度综述了近年来网络控制系统的研究成果和最新进展。最后,针对网络控制系统兼具网络和控制的特点,提出了网络与控制两者相结合分析网络控制系统的新方法。     

Stochastic fault tolerant control of networked control systems

A problem of stabilization about uncertain networked control systems (NCSs) with random but bounded delays is discussed in this paper. By using augmented state-space method, this class of problems can be modeled as discrete-time jump linear systems governed by finite-state Markov chains. A new switched model based on probability is proposed to research problems of reliable control when actuators become ageing or partially disabled. Using improved V-K iteration algorithm, a class of reliable controllers are designed to make systems asymptotically mean square stable under several stochastic disturbances such as random time-delay and stochastic actuator failure and the maximal redundancy degree is given through this method.     

A novel controller design and evaluation for networked control systems with time-variant delays

A new delayed state-variable model for networked control systems is presented, upon which a linear quadratic regulator (LQR) is designed. A method of delays-estimation online is also given. A fuzzy logic with LQR controller is addressed for the difficulty on implementation of LQR in networked control systems (NCSs) with time-variant delays. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.     

H∞ guaranteed cost control for uncertain Markovian jump systems with mode-dependent distributed delays and input delays

This paper investigates the H_∞ guaranteed cost control problem for mode-dependent time-delay jump systems with norm-bounded uncertain parameters. Both distributed delays and input delays appear in the system model. Based on a matrix inequality, a sufficient condition for the existence of robust H_∞ guaranteed cost controller is derived, which stabilizes the considered system and guarantees that both the H_∞ performance level and a cost function have upper bounds for all admissible uncertainties. By the cone complementary linearization approach, the desired state-feedback controller can be constructed. A numerical example is provided to show the effectiveness of the proposed theoretical results.     

Optimal LQG controller for linear stochastic systems with unknown parameters

This paper presents the optimal LQG controller for linear systems with unknown parameters. The optimal controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. Performance of the obtained optimal controller is verified in the illustrative example against the conventional LQG controller that is optimal for linear systems with known parameters. Simulation graphs verifying overall performance and computational accuracy of the designed optimal controller are included.     

Observer based fault-tolerant control for a class of nonlinear networked control systems

In this paper, we present a fault-tolerant control (FTC) framework for a class of nonlinear networked control systems (NCSs). Firstly, the plant is transformed into two subsystems with one of them decoupled from the system fault. Then, the nonlinear observer is designed to provide the estimation of unmeasurable state and modelling uncertainty, which are used to construct fault estimation algorithm. Considering the sampling intervals occurred by net, a fault-tolerant control method is proposed for such nonlinear NCSs using the impulsive system techniques. The controller gain and the maximum sampling interval, which make the faulty system stable are given. An example is included to show the efficiency of the proposed method.     

Optimal controller for uncertain stochastic polynomial systems

This paper presents the optimal quadratic-Gaussian controller for uncertain stochastic polynomial systems with linear control input and a quadratic criterion over linear observations. The optimal closed-form controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. As intermediate results, the paper gives closed-form solutions of the optimal regulator and controller problems for stochastic polynomial systems with linear control input and a quadratic criterion. Performance of the obtained optimal controller is verified in the illustrative example against the conventional quadratic-Gaussian controller that is optimal for stochastic polynomial systems with known parameters. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.     

一类线性切换系统的鲁棒跟踪控制

文章研究了线性切换系统的鲁棒跟踪控制,并提出可解性的充分条件。设计切换控制规则使得切换线性系统满足加权H∞参考模型,并采用平均驻留时间法和Lyapunov函数来处理稳定性分析和控制器设计。通过使用线性矩阵不等式,控制器设计问题可以得到很好的解决。     

A delay distribution based stability analysis and synthesis approach for networked control systems

Communication delays in networked control systems (NCSs) has been shown to have non-uniform distribution and multifractal nature. This paper proposes a delay distribution based stability analysis and synthesis approach for NCSs with non-uniform distribution characteristics of network communication delays. A stochastic control model related with the characteristics of communication networks is established to describe the NCSs. Then, delay distribution-dependent NCS stability criteria are derived in the form of linear matrix inequalities (LMIs). Also, the maximum allowable upper delay bound and controller feedback gain can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples showed that the results derived from the proposed method are less conservativeness than those derived from the existing methods.     

Control structure design of networked control systems based on maximum allowable delay bounds

In this work, we present a control structure based on the maximum allowable delay bound of networked control systems that takes the network-induced delay into account. Control structure design deals with the structural decisions of the control system including where to place the controllers and how to harmonize them. We construct a hierarchical control structure that consists of a main controller and a local closed-loop system consisting of a family of control configurations. Based on the maximum allowable delay bound for each local configuration, the local supervisor orchestrates switching between the constituent configurations. The stability condition is derived based on common Lyapunov function technique. An example is presented to demonstrated the efficacy of the proposed approach.     

Non-fragile guaranteed cost control for uncertain stochastic nonlinear time-delay systems

This paper deals with the problem of non-fragile guaranteed cost control for a class of uncertain stochastic nonlinear time-delay systems. The parametric uncertainties are assumed to be time-varying and norm bounded. The time-delay factors are unknown and time-varying with known bounds. The aim of this paper is to design a memoryless non-fragile state feedback control law such that the closed-loop system is stochastically asymptotically stable in the mean square for all admissible parameter uncertainties and the closed-loop cost function value is not more than a specified upper bound. A new sufficient condition for the existence of such controllers is presented based on the linear matrix inequality (LMI) approach. Then, a convex optimization problem is formulated to select the optimal guaranteed cost controller which minimizes the upper bound of the closed-loop cost function. Numerical example is given to illustrate the effectiveness of the developed techniques.