随机分组策略下的分布式多智能体一致性

多智能体分布式一致性算法一般需要获得相对状态差值x_i-x_j,本文针对无法得到智能体间相对状态差值的情况,提出一种基于智能体分组,通过组间信息交换来达到智能体状态一致的算法.本文仅讨论离散情况下智能体被随机划分为两组和多组的情况.当存在两个随机分组时,每个智能体都进行状态更新,且更新量为组间的状态差值.此时,系统达到期望一致的充要条件为所给出的状态更新参数应大于1.当存在多个随机分组时,仅通过Gossip算法选中的两组智能体以这两组间的状态差值进行状态更新.在这种情况下,系统达到期望一致的充分条件为各分组概率相等,且状态更新参数大于1.最后通过计算机仿真验证了结论的正确性.     

基于多点非均匀变异的多目标极值优化算法研究

多目标进化算法因其在解决含有多个矛盾目标函数的多目标优化问题中的强大处理能力,正受到越来越多的关注与研究。极值优化作为一种新型的进化算法,已在各种离散优化、连续优化测试函数以及工程优化问题中得到了较为成功的应用,但有关多目标EO算法的研究却十分有限。本文将采用Pareto优化的基本原理引入到极值优化算法中,提出一种求解连续多目标优化问题的基于多点非均匀变异的多目标极值优化算法。通过对六个国际公认的连续多目标优化测试函数的仿真实验结果表明：本文提出算法相比NSGA-II、 PAES、SPEA和SPEA2等经典多目标优化算法在收敛性和分布性方面均具有优势。     

非均匀热传递下传感网络节点选择改进算法

在非均匀热传递网络通信效率优化的研究中,由于非均匀热传递环境下的传感网络中的节点的能力消耗过程具有较强的随机性和动态性特征,使得节点能量消耗出现不规则发散问题.传统的传感网络节点选择以既定节点能量分布为前提,没有考虑温度造成的节点不规则能耗造成的能量下降问题,使得节点选择过程存在弊端.提出了一种自适应模糊差分和自适应粒子群的传感网络节点选择改进算法,分析非均匀热环境下传感网络通信原理,得到非均匀热传递下传感网络节点能量特征,依据节点的能量特征,自适应完成非均匀热传感网络簇首的选择,采用Logistics模糊映射对节点进行改进分区处理,获取最佳网络节点分区,将模糊扰动量融入最佳节点分区中,采用自适应粒子群算法对无线传感网络最佳分区节点的最优位置进行运算,获取无线传感网络最佳能量节点的最优位置,实现网络节点覆盖改进.仿真结果说明,所提算法可在非均匀热传递环境下实现传感网络节点节点的改进,具有较高的收敛效率.     

非均匀演化算法及其应用

提出一种基于非均匀变异的演化算法模型;基于随机过程理论分析了该算法的自适应性,用该算法求解了实际的“油层结垢”问题;基于随机优化领域经典的高维多峰测试函数,同已有的同类算法做了对比.实验结果表明：在没有引入任何额外参数和计算的前提下,该算法具有更好的收敛性和稳定性.     

输出死区下的随机多智能体系统一致性饱和控制

针对一类存在输入饱和和输出死区现象的非严格反馈非线性随机多智能体系统,提出一种自适应神经网络一致性饱和控制算法.首先,为了解决非对称输入饱和问题,构造一类与所考虑智能体相同阶次的辅助系统;然后,以反步法和辅助系统作为框架,利用神经网络处理系统中的未知非线性函数,并结合Nussbaum函数解决输出死区问题;接着,利用动态面控制技术避免“计算爆炸”问题;然后,基于李雅普诺夫稳定性理论验证所提出的控制算法能够保证闭环系统全部信号依概率半全局一致最终有界;最后,通过数值仿真和实例仿真的结果验证所提出控制算法的有效性.     

离散线性一致性算法噪声问题研究

多智能体一致性问题在传感网、社交网、协同控制等诸多领域有着广泛的实际应用背景, 本文对离散线性一致性算法的噪声问题进行了研究, 证明了离散线性 一致性算法的噪声不可控性; 提出基于抑噪算子ε(t)的噪声控制策略, 指出当ε(t)为t-0.5的高阶无穷小时, 抑噪后的一致性算法噪声可控; 分析了抑噪算子对一致性 算法收敛性的影响, 证明了在无噪声条件下, 当抑噪算子ε(t为t-1的低阶无穷小时, 抑噪后的一致性算法依然可以使Agent收敛至原收敛状态x*.在上述结论基础上进一步指出, 当t→∞ 时, 若抑噪算子ε(t)的阶在t-0.5~t-1之间, 所有Agent 的状态将以原收敛状态x* 为中心呈正态分布. 最后, 以DHA 为例对相应理论结果进行了验证和讨论. 本文为线性一致性算法的噪声控制提供了理论依据, 对抑噪算s子的确定有较强的指导意义.     

多智能体系统分布式一致性算法研究现状

综述了多智能体系统分布式一致性问题的研究现状。从理论层面介绍了一致性问题的几种常见定义及与特性相关的主要参数;总结归纳了近年来几种一致性协议及其理论分析结果;分析和阐述了一致性问题的主要应用领域的进展。展望了未来的研究方向。     

基于事件驱动的二次凸优化问题分布式优化算法

针对多智能体系统中等式约束下的二次凸优化问题,给出一种事件驱动机制下的分布式优化算法.该算法可以降低每个智能体控制协议的更新频率以及智能体之间的通信负担.基于图论和李雅普诺夫函数方法给出两种不同的事件触发条件,其中第2种事件触发条件不需要拉普拉斯矩阵的最大特征根的信息,可实现算法全分布式实施.两种事件触发条件均可实现算法渐近收敛到优化值,避免智能体控制协议的连续更新以及智能体之间的连续通信,同时保证每个智能体相邻事件触发时刻的时间间隔大于0,避免持续事件触发.将所提出的算法应用于Matlab仿真环境中进行仿真验证,仿真结果验证了所提出算法的有效性.     

非平衡有向网络下带约束的连续时间分布式优化算法设计EI北大核心CSCD

本文基于权重不平衡有向网络,对一类分布式约束优化问题进行研究,其中全局目标函数等于具有李普希兹梯度的强凸目标函数之和,并且每个智能体的状态都有一个局部约束集.每个智能体仅知道自身的局部目标函数和非空约束集.本文的目标是用分布式方法求解该问题的最优解.针对优化问题,提出了一种新的分布式投影梯度连续时间协调算法,利用拉普拉斯矩阵的零特征值对应的左特征向量消除了图的不平衡性.在某些假设下,结合凸分析理论和李雅普诺夫稳定性理论,证明了算法能够获得问题的最优解.最后,通过仿真验证了算法的有效性.     

随机拓扑结构下多智能体系统的平均一致性*

利用马尔可夫收敛准则、图的Laplace矩阵谱特性和欧氏度量的极值,对一类具有随机拓扑结构的离散时间多智能体系统平均一致性问题进行了深入讨论。引入完好概率矩阵的概念,建立随机拓扑结构下离散时间系统的一致性算法,应用马尔可夫过程收敛相关结论及伴随算子,从欧氏度量极值的角度证明了系统可达到渐近平均一致,并得出了所需满足的条件,该条件放宽了对系统连通性的要求。最后,采用六个智能体组成的多智能体系统进行计算机仿真,对理论的正确性进行了验证。     

离散高阶分布式一致性算法

为了提高分布式一致性算法的收敛速度, 提出了一种离散高阶分布式一致性算法。该算法通过单跳通信, 利用二跳邻接节点的前多步信息来加速分布式一致性算法的收敛速度。对无向通信拓扑下该算法的收敛性能和收敛速度, 以及带通信延时的该算法的收敛性能进行了分析和仿真比较, 结果显示, 该算法在满足条件下能收敛到初始状态的平均值, 与同样利用二跳邻接节点信息的算法相比, 具有通信量小, 收敛速度更快的特点, 但是能容忍的通信延时变小。     

Asynchronous sampled-data consensus of singular multi-agent systems based on event-triggered strategy

This paper is concerned with sampled-data consensus for multi-agent systems with singular dynamics. It is assumed that the sampling period of each agent is independent of the other's. Based on event-triggered sampled-data transmission strategy, a distributed consensus protocol is presented. The consensus of singular multi-agent system is transformed into the stability of singular systems with multiple time-varying delays. By employing the Lyapunov-Krasovskii functional method, a sufficient condition on the consensus of multi-agent singular system is derived. Based on the obtained condition, an algorithm to design consensus controller gains is presented in terms of linear matrix inequalities. Two numerical examples are given to show the effectiveness of the proposed method.     

伪多跳中继分布式一致性算法

为了提高分布式一致性问题的收敛速度, 减少节点间的通信成本, 本文提出一种分布式一致性算法. 新算法采用单跳通信, 利用非邻接节点的前状态信息进行节点状态更新. 本文证明了在无向通信拓扑下新算法的一致性收敛, 并分析计算了新算法的通信量以及收敛速度的变化. 通过理论分析和仿真验证, 结果表明新算法具有收敛速度快, 通信方式简单, 通信量少, 存在通信延时情况下通信数据不容易丢失等优点.     

Asynchronous consensus of multiple second-order agents with partial state information

This article studies the asynchronous consensus problem of multiple second-order agents in a sampled-data setting, where asynchrony means that the sampling period of each agent is independent of the others. It is assumed that each agent can only obtain the information of its positions relative to its neighbours at sampling instants. First, a discrete-time protocol is provided based on velocity estimation, and a sufficient and necessary condition for consensus under this protocol is established in virtue of properties of periodic systems. Second, a continuous-time protocol is presented by the theory of dynamic output feedback control, and a sufficient condition for consensus under this protocol is obtained by applying an input delay approach. Simulations are performed to illustrate the effectiveness of the theoretical results.     

Asynchronous consensus of continuous-time multi-agent systems with intermittent measurements

This article is concerned with asynchronous consensus problems of continuous-time second-order agents with fixed topology and time-varying delays. It is assumed that each agent obtains the measurements of its states relative to its neighbours only at discrete times and the discrete times of each agent are independent of the others'. It is proven that the asynchronous consensus is equivalent to the global asymptotic stability of a time-varying discrete-time system with delays. Furthermore, a sufficient condition for asynchronous consensus is established in virtue of the Lyapunov's direct method. Simulations are performed to validate the theoretical results.     

Robust consensus algorithm for second-order multi-agent systems with external disturbances

This article investigates the problem of robust consensus for second-order multi-agent systems with external disturbances. Based on a non-smooth backstepping control technique, a class of novel continuous non-smooth consensus algorithms are proposed for the multi-agent network with/without communication delays. The controller design is divided into two steps. First, for the kinematic subsystem, the velocity is regarded as a virtual input and designed such that the states consensus can be achieved asymptotically. Then for the dynamic subsystem, a finite-time control law is designed such that the virtual velocity can be tracked by the real velocity in a finite time. Under the proposed control law, it is shown that if the communication topology graph contains a directed spanning tree, the states consensus can be achieved asymptotically in the absence of disturbances. In the presence of disturbances, the steady-state errors of any two agents can reach a small region around the origin. By building a relationship between control parameters and the bound of steady tracking errors, it is demonstrated that the disturbance rejection performance of the resulting closed-loop system can be enhanced by adjusting the fractional power in the non-smooth controller. Finally, an example is given to verify the efficiency of the proposed method.     

Robust consensus algorithm for multi-agent systems with exogenous disturbances under convergence conditions

In this paper, a robust consensus algorithm is developed and sufficient conditions for convergence to consensus are proposed for a multi-agent system (MAS) with exogenous disturbances subject to partial information. By utilizing H_∞ robust control, differential game theory and a design-based approach, the consensus problem of the MAS with exogenous bounded interference is resolved and the disturbances are restrained, simultaneously. Attention is focused on designing an H_∞ robust controller (the robust consensus algorithm) based on minimisation of our proposed rational and individual cost functions according to goals of the MAS. Furthermore, sufficient conditions for convergence of the robust consensus algorithm are given. An example is employed to demonstrate that our results are effective and more capable to restrain exogenous disturbances than the existing literature.     

区块链共识算法研究综述

共识算法是区块链系统维护数据一致性的核心机制.本文深入调研并分析了具有代表性的共识算法及其演化历程;基于共识过程提出共识算法的分类模型,并对各类型中代表性的共识算法进行详细分析;最后从去中心化、可扩展性、安全性、一致性、可用性、分区容忍性六个方面建立了一套共识算法的评价指标体系,并对代表性的共识算法进行对比分析,给出各...