Leader-following consensus of fractional-order multi-agent systems via adaptive control

This article focuses on the consensus problem of leader-following fractional-order multi-agent systems (MASs) with general linear and Lipschitz nonlinear dynamics. First, the distributed adaptive protocols for linear and nonlinear fractional-order MASs are constructed, respectively. We allow the control coupling gains to be time varying for each agent. Moreover, the adaptive modification schemes for the control gain are designed, which renders smaller control gains and thus requires smaller amplitude on the control input without sacrificing consensus convergence. Second, based on fractional-order Lyapunov stability theorem and Barbalat's lemma, two novel sufficient conditions in terms of linear matrix inequalities are provided to ensure that the leader-following consensus can be obtained in the case for any undirected connected communication graph. Furthermore, we show that the proposed algorithm also works for consensus of agents with intrinsic Lipschitz nonlinear dynamics. As a result, the proposed framework requires no global information and thus can be implemented in a fully distributed manner. Finally, the numerical simulations are given to demonstrate the effectiveness of obtained the theoretical results.     

Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays

In this paper, we discuss average consensus problem in undirected networks of dynamic agents with fixed and switching topologies as well as multiple time-varying communication delays. By employing a linear matrix inequality method, we prove that all the nodes in the network achieve average consensus asymptotically for appropriate communication delays if the network topology is connected. Particularly, several feasible linear matrix inequalities are established to determine the maximal allowable upper bound of time-varying communication delays. Numerical examples are given to demonstrate the effectiveness and the sharpness of the theoretical results.     

Pi-coefficient analysis of update algorithms for adaptive systems

This paper finds the appropriate pi-coefficients for a parameter estimation adaptive system and uses them to analyze the stability of two estimation algorithms. The estimation error dynamics of the system are modeled by a linear time-invariant subsystem and a nonlinear time-varying update law in a feedback loop. Then the so-called max-p problems are formulated and solved to obtain the pi-coefficients for the linear subsystem and nonlinear update low. For the investigated system, the quantitative results show that the least-squares update algorithm has larger stability range than that of the gradient algorithm, and the σ-modification scheme gives larger stability ranges for both algorithms.     

异构空间信息的分级共识模型研究

Internet上异构、分布的空间信息因各自独立、相对封闭而无法相互沟通和协作,从而形成了空间信息孤岛。论文利用计算机的知识表示理论和Ontology技术能够明确表达相关领域共识的特点,探索性地提出了异构空间信息的分级共识模型。该模型为解决上述问题提供了一条切实可行的新思路。     

一种基于门限签名的区块链共识算法

针对区块链应用于物联网环境下的特点和要求,分析了目前广泛应用于联盟链的实用拜占庭容错算法（PBFT）的弊端以及目前应用于共识网络中的门限签名算法存在的普遍问题,提出改进的共识算法。首先,新共识机制将网络中的节点分组用部分节点的两两通信代替所有节点的两两通信减少通信量;其次,将组合公钥的思想引入到门限签名中,减少了通信量与计算量;最后,在节点之间引入信用分机制,优化视图切换协议。仿真结果表明,新提出的共识算法在数据吞吐量以及通信时延方面有了明显的提升,并且得到了通信量最低时的最佳分组方式。     

微博影响力评价研究

微博作为一种被广泛使用的网络平台,其多样的特性满足了人们信息获取、人际交流等多方面的新需求,微博已成为人们日常生活的重要组成部分之一。微博影响力作为微博研究的一个热点,对于优化微博的信息整合、传输,对于深入了解微博发展方向、维护网络内容安全、促进网络发展具有非常重要的理论和实践意义。文章对当前主要的微博影响力评价方法进行了梳理和分析,并提出了针对中国微博的影响力评价模型。     

具有随机丢包的网络化多自主体系统的一致性

研究具有随机丢包的网络化多自主体系统的均方一致性问题,其中不同自主体间的通信通道具有相同的丢包情况并且均服从马尔可夫(Markov)分布。首先,利用系统变换和迭代方法,得到了系统达到均方一致的一个初等充要条件。然后,利用矩阵理论和图论知识,如果拓扑图含有有向生成树,则可以将系统的均方一致性转化成一个线性Markov跳变系统的均方稳定性,并且可以建立线性矩阵不等式形式的均方可镇定准则。最后,通过相应的仿真实例说明了所得结论的可行性。     

计及灵活性储备的含风电多微电网系统分布式协调调控策略

高比例风电的接入和需求响应技术的应用对分布式架构下的多微电网系统有功功率动态平衡提出了更高的要求,有必要充分利用灵活性资源对系统进行协调调控.提出一种新颖的灵活性电池储备模型对多微电网系统灵活性备用容量进行评估,定义虚拟灵活性电池储备模型对风电场备用与需求响应负荷备用进行评估,充分挖掘其调频的潜在能力.在此基础上,基于一致性算法求解该模型下各微电网的功率分配,提出计及灵活性储备的含风电多微电网系统分布式协调调控策略,实现分布式架构下灵活性资源的协调优化.通过华东某地区实际数据验证了所提策略的有效性.算例结果表明,协调优化源-荷灵活性储备资源在保障风电消纳的同时,实现了分布式架构下系统的动态功率平衡.