具有通信时延的离散时间二阶多个体网络的一致性问题

针对具有通信时延的离散时间二阶多个体系统的一致性问题,采用了具有静态领导者的一致性算法.根据广义Nyquist判据和Gerschgorin圆盘定理,得到了系统渐近收敛到领导者状态的充分条件.在个体与领导者构成的连接拓扑满足一定连通性的前提下,该充分条件是分散形式的,与控制参数、邻居个体之间的连接权值相关,而与通信时延大小无关.仿真结果证明了结论的正确性.     

Consensus of linear conformable fractional order multi-agent systems with impulsive control protocols

In this article, we study the impulsive consensus problem of linear multi-agent systems composed of α-order conformable differential equations (α ∈ (0, 1]). Two cases of fixed and switching interaction networks are considered, respectively. Impulsive protocol of each agent is introduced based on the local information of the interaction networks. Firstly, we derive the analytic solution of the general linear conformable systems with impulses. Secondly, two sufficient criterions are presented to guarantee the convergence of the consistent state for all the agents by using matrix theory, graph theory, and impulsive control theory. Finally, three numerical simulations are provided to demonstrate the obtained theoretical results and to compare the convergence rates of the systems with distinct orders.     

基于Q-learning的离散时间多智能体系统一致性

针对模型未知的一类离散时间多智能体系统,本文提出了一种Q-learning方法实现多智能体系统的一致性控制.该方法不依赖于系统模型,能够利用系统数据迭代求解出可使给定目标函数最小的控制律,使所有智能体的状态实现一致.通过各个智能体所产生的系统数据,采用策略迭代的方法实时更新求解得到多智能体系统的控制律,并对所提Q-le...     

受干预多智能体系统的一致性分析及控制

运用图论、矩阵分析和极限理论, 研究当通信拓扑结构连通的多智能体系统受到干预时, 系统仍保持一致性的充分条件及其平衡状态. 利用指数函数快速递减且可积的特性, 设计干预控制器, 控制多智能体系统收敛到指定位置. 仿真研究实验验证了所提出结论的正确性.

     

具有切换拓扑的多智能体系统协同控制的差分隐私保护

网络信息技术的不断发展与普及使得各类数据的发布采集变得方便与便捷, 但数据的直接发布势必会造成个网络信息的泄露和敏感信息的失密, 因此敏感信息的保护成为了各行各业关注的问题. 本文研究了基于固定拓扑和切换拓扑的多智能体系统协同控制的差分隐私保护问题, 将差分隐私算法与传统平均一致性算法结合, 提出了具有隐私保护的协同控制算法, 分析了隐私保护算法对分布式协同控制闭环系统稳定性的影响. 基于所提算法, 应用矩阵论和概率统计对隐私保护协同控制算法的收敛性和隐私性进行理论分析, 该算法可以保护智能个体的数据隐私, 同时可以使得系统运动实现均方一致. 在系统拓扑结构动态变化的情况下, 本文对该算法的收敛性和隐私性进行理论分析, 讨论了切换拓扑对隐私保护的影响. 最后的仿真示例验证了理论结果的正确性.     

高阶时滞多智能体系统一致性控制

本文讨论了多输入网络化时滞多智能体系统的一致性问题.应用无向或有向图描述网络化系统的拓扑结构.多智能体的一致性收敛问题可以转化为线性时滞系统的稳定性问题.通过双线性矩阵不等式可以得到高阶多智能体系统时滞相依以及时滞独立的一致性准则.最后,举例一个无向拓扑结构的时滞多智能体来说明本文方法的有效性.     

寻找多智能体系统一致性的迭代学习方法

本文利用迭代学习的方法研究了带头结点的多智能体系统的一致性问题.文中分别对单积分多智能体系统和一般的线性多智能体系统提出了迭代学习型的一致性算法.该算法对每一个从节点所设计的分布迭代学习序列可以保证从节点能完全跟随上头结点.假设头结点是全局可达的,对于有向拓扑连接图,给出了智能体达到完全一致的充分条件.最后,仿真实例说明了文中所给方法的有效性.     

Event-triggered control for discrete-time multi-agent average consensus

We consider the average consensus problem for the multi-agent system in the discrete-time domain. Three triggering based control protocols are developed, which dictate the broadcast and control update instants of individual agents to alleviate communication and computational burden. Lyapunov-based design methods prescribe when agents should communicate and update their control so that the network converges to the average of agents' initial states. We start with a static version of the distributed event-triggering law and then generalize it so that it involves an internal auxiliary variable to regulate the threshold dynamically for each agent. The third protocol uses a self-triggering algorithm to avoid continuous listening wherein each agent estimates its next triggering time and broadcasts it to its neighbors at the current triggering time. Numerical simulations are shown to validate the efficacy of the proposed algorithms.     

Consensus of multi-agent systems based on sampled-data control

This article studies the consensus problem in directed networks, assuming that each agent is with double-integrator dynamics and only obtains the measurements of its positions relative to its neighbours at sampling instants. We propose a protocol based on sampled-data control and derive an equivalent characterisation of the solvability of the consensus problem under this protocol. In virtue of this equivalent characterisation, we further consider two cases: fixed topology and switching topology. For the first case, we present a set of sampling periods and feedback coefficients which ensure that the protocol can solve a consensus problem. For the second case, we derive sufficient conditions for the protocol to solve a consensus problem under arbitrary switching signals and under a class of switching signals, respectively. Finally, simulations are provided to illustrate the effectiveness of the theoretical results.     

离散多智能体系统分组一致性研究

针对一阶、二阶离散多智能体系统的分组一致性问题进行了研究。为了去除了现有结果的一些保守假设,提出了两个新的分组一致性协议,新的协议反映了系统相同分组内与不同分组间智能体的相互影响。基于图论和稳定性理论,经过分析得到了两个保证系统一致的充分条件。最后,通过两个仿真实例证明了理论结果的有效性。     

Consensus of multi-agent linear dynamic systems via impulsive control protocols

In this article, we introduce impulsive control protocols for multi-agent linear dynamic systems. First, an impulsive control protocol is designed for network with fixed topology based on the local information of agents. Then sufficient conditions are given to guarantee the consensus of the multi-agent linear dynamic systems by the theory of impulsive systems. Furthermore, how to select the discrete instants and impulsive matrices is discussed. The case that the topologies of networks are switching is also considered. Numerical simulations show the effectiveness of our theoretical results.     

受未知通信时滞影响的高阶多智能体系统的趋同

本文考虑了极点在闭左半平面的高阶连续多智能体系统的趋同问题.假设网络拓扑为有向图,且个体从邻居收到的信息存在通信时滞,分别得到与时滞无关和与时滞有关的两种趋同条件,这两个条件充分揭示了智能体结构、通信时滞和网络拓扑三者之间的关系.本文的核心方法是利用参数化代数Riccati方程的唯一正定解来设计趋同增益.此外,文中说明了通信时滞在有些情况下可为时变的.最后,数值例子验证了所得理论结果的有效性.     

一类离散时间异构多智能体系统的一致平衡点分析

针对包含一阶二阶智能体的异构系统, 提出一种线性一致性协议. 利用图论和矩阵分析方法分析系统获得一致性的充分条件和一致平衡点, 并证明仅网络中的根节点对平衡点起作用. 在此基础上, 分析平衡点的取值范围,通过参数优化可以使系统收敛到该范围内任意给定的期望值. 最后, 通过仿真分析表明了理论分析的正确性.

     

Consensus recovery of multi-agent systems subjected to failures

Consensus recovery is one of the most important topics of multi-agent systems subjected to failures, but there are few literatures considering this theme. In this article, two disastrous failures are introduced and corresponding recovery programs are proposed to investigate the consensus recovery of multi-agent systems. The failures of multi-agent systems mainly refer to the failures to the agents and links. The cut-agent and cut-link are presented to better understand the disastrous failures of multi-agent systems, and they are the most important components of multi-agent systems. When the cut-agent and cut-link are removed from the systems, the multi-agent systems will become disconnected, and the neighbour agents of cut-agent are used to recover the consensus of multi-agent systems in this article. For different failures, the different measures are taken to restore the connectivity of multi-agent systems, so as to recover the consensus of multi-agent systems. Under the proposed recovery strategies, the convergence speed of achieving consensus of the resulting networks is considered as the main target. Moreover, there is a trade-off between the convergence speed and robustness of the resulting networks.     

Constrained consensus of discrete-time multi-agent systems with time delay

In this paper, we consider the consensus conditions for discrete-time multi-agent systems with communication delay between agents, subject to that each agent's state is constrained to lie in a given convex set. And we will present some consensus conditions for unconstrained multi-agent systems with time delay.     

非平衡拓扑结构的多智能体网络系统一致性协议

针对多智能体网络系统,本文分别研究了非平衡拓扑结构的多智能体连续状态和离散状态下的一致性协议.首先提出了能使用有向图表示的多智能体网络系统的拓扑结构,并根据该拓扑结构建立了网络系统的1阶数学模型和提出了多智能体网络系统一致收敛准则.对于多智能体网络连续系统,该系统的一致平衡点最终收敛于初始状态的凸组合,本文最终确定了非平衡拓扑结构的一致平衡点.如果多智能体网络系统的拓扑结构没有改变,在离散状态下系统的一致平衡点仍收敛于初始状态的凸组合,并且离散状态下系统的一致平衡点与连续状态下系统的一致平衡点相等.最后采用8个智能体组成的网络拓扑进行计算机仿真,验证理论的正确性.     

Interval observer-based consensus control of discrete-time multi-agent systems under stealthy attacks

In this paper, interval observer-based consensus control is developed for multi-agent systems with unknown input signals, sensor noises, and stealthy attack signals. Compared with the conventional robust observer, the interval observer has more relaxed preconditions for the systems, so the interval observer is more extensive. First, design an interval observer for each subsystem and linearly transform into a form that is easy to obtain the coefficient matrices of the interval observer. Then, based on the upper bound estimation of the observer, design a consensus control protocol, and the $H_{\infty }$ technique is used to suppress the unknown input signals. Finally, a numerical simulation example is presented to illustrate the feasibility and correctness of the developed method.     

Consensus of networked multi-agent systems with communication delays based on the networked predictive control scheme

The consensus problem of discrete-time networked multi-agent systems (NMASs) with a communication delay is investigated in this article, where the dynamics of agents described by discrete-time linear time-invariant systems can be either uniform or non-uniform. For the NMASs with a directed topology and constant delay, a novel protocol based on the networked predictive control scheme is proposed to compensate for communication delay actively. Using algebraic graph theories and matrix theories, necessary and/or sufficient conditions of achieving consensus are obtained, which indicates that, under the proposed protocol, the consensus is independent of the network delay and only dominated by agents' dynamics and communication topology. Meanwhile, the protocol design and consensus analysis are also presented in the case of no network delay. Simulation results are further presented to demonstrate the effectiveness of theoretical results.     

受外界干扰的离散多智能体系统的均方有界一致性

对有外界干扰的二阶离散多智能体系统,研究了在马尔可夫切换拓扑结构下的均方有界一致性问题.首先,设计了一个带有智能体位置和速度信息的控制协议.其次,在随机有界干扰的情况下,借助于矩阵分析方法以及Lyapunov函数,得到了闭环系统实现均方有界一致所需的代数条件,同时给出了各智能体状态误差的上界.最后,数值仿真验证了理论结果的有效性.