端口受控哈密顿多智能体系统的输出一致性协议设计

研究了端口受控哈密顿（PCH）多智能体系统分别在固定和切换拓扑下的输出一致性问题. 首先根据哈密顿系统特有的优势,运用能量整形思路设计了一个全局稳定的群组输出一致性协议,该协议通过构造虚拟邻居的方式将有向图转化成无向图. 其次通过利用推广的LaSalle's不变原理将切换拓扑的问题转化成切换系统来研究. 例子证明,本文很好的解决端口受控哈密顿（PCH）多智能体系统的输出一致性问题.     

一类异构多智能体系统一致性协议的收敛性分析

针对一阶二阶智能体组成的异构多智能体系统,采用了一种线性一致性协议,基于图论和矩阵分析的方法对一致性协议的收敛性进行研究,得出了一致性协议最终收敛值的表达式,并给出了收敛区间,通过参数优化设置可以实现系统收敛到该区间内任意给定的期望值.最后在仿真实例中,实现了异构多机器人系统在期望位置的聚集,仿真结果验证了理论分析的正确性.     

一类异构多智能体系非线性协议下的一致性分析

针对一阶、二阶混合异构多智能体系统一致性问题研究中,存在状态不可测和系统最终仅可以获得静态一致性的问题,提出了一种具有参考速度的非线性一致性协议.在此基础上,首先,将一致性分析转化为稳定性证明;然后,构造李亚普诺夫函数;最后,基于李亚普诺夫稳定性理论和拉塞尔不变集原理,分析得出了该异构系统获得一致性的充分条件.仿真结果表明,满足文中的条件,系统在所提出的协议下获得了一致性.     

有向图中基于扰动观测器的线性多智能体系统一致性

在有向图中,针对多智能体系统中智能体动力学存在扰动的情形,研究了系统的一致性问题.每个智能体的动力学模型为存在未知外部扰动的一般线性系统.在有向图是强连通的条件下,通过设计一种基于扰动观测器的分布式算法,实现了存在未知扰动的线性多智能体系统的一致性.最后通过仿真验证所提算法的有效性.     

基于二阶邻居事件触发多智能体系统的一致性

针对多智能体系统的平均一致性问题,采用二阶邻居信息设计一致性协议以加速一致性收敛速度。同时,为了减少系统的通信次数,基于事件控制的方法被用于一致性协议的设计中。首先在固定拓扑网络下研究了多智能体系统利用二阶邻居信息来加速一致性收敛速度的问题,随后在切换拓扑网络下对类似问题进行了分析。最后,把该协议应用到数值仿真中,并与只利用一阶邻居信息的协议比较,仿真结果表明所设计的协议能够加快收敛速度。     

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.     

事件触发下多智能体系统固定时间二分一致性

针对具有符号有向图的一阶多智能体系统,研究了其固定时间二分一致性问题。为降低控制过程中多智能体系统的能量损耗,提出了一种基于事件触发机制的分布式控制协议。以图论和李雅普诺夫理论为主要研究工具,给出了多智能体系统在所设计控制协议作用下实现固定时间二分一致性的充分条件和与系统初始状态无关的收敛时间上界,并证明了使用该协议可以有效避免对智能体的连续控制和Zeno行为的发生。数值算例验证了所得理论结果的有效性。     

速度不可测的异构多智能体系统一致性分析

近年来,随着异构系统在实际中的广泛应用,异构多智能体系统一致性分析成为研究热点。针对一阶部分智能体控制输入有界、二阶智能体速度不可测的异构多智能体系统,在无向网络拓扑图下给出了无领导者和有领导者两种控制输入设计方法,基于图论知识和LaSalle不变集原理给出了该异构系统实现一致性的充分条件。最后,通过数值仿真验证了该理论的正确性。     

离散时间混合多智能体的拟平均一致性控制

为了研究混合一阶和二阶异质无向多智能体网络离散时间一致性问题,提出了固定和可变拓扑结构的多智能体网络的拟平均一致性协议.根据Lyapunov函数和代数图论,分析了多智能体网络的稳定性,表明在固定和可变拓扑结构的情况下,混合阶多智能体系统可以达到拟平均一致.对6个节点组成的4种不同的无向网络拓扑结构进行了仿真,结果显示了变拓扑离散时间异质多智能体网络的位置和速度均能达到拟平均一致.仿真结果表明,该算法对混合阶多智能体网络的拟平均一致性控制有效.     

基于公共邻居的MHK一致性协议及其稳定性分析

如何增强多智能体系统一致性收敛是其一致性研究的重要问题。提出了一种新的MHK（multi-agent-based Hegselmann-Krause）一致性协议,该协议将智能体间的公共邻居作为切换网络下多智能体分布式协作的重要调控因素。针对该协议下的多智能体系统设计了能量函数,分析并证明了该系统具有李雅普诺夫意义下的稳定性,将收敛为一个或多个子观点集群。数值仿真采用增量分析方法考察了系统所收敛的观点集群数量与初始拓扑区间长度的关系;实验表明,该协议使多智能体系统收敛为数量更少的观点集群。所提出的基于公共邻居的MHK一致性协议能够有效提高切换网络的连通性,从而增强系统的一致性收敛,并能为观点演化模型的控制与优化提供理论支撑。     

Average consensus of continuous‐time multi‐agent systems with quantized communication

This paper focuses on the average consensus problem of first‐order and second‐order continuous‐time multi‐agent systems with logarithmic quantized information transmission. The balanced and strongly connected digraphs are utilized to characterize the interaction topologies between agents. Based on the state estimation, distributed state updating mechanisms are introduced for every agent such that all agents’ states achieve average consensus asymptotically. By means of differential inclusion theory, we discuss the existence and convergence property of the Krasovskii solutions to the closed‐loop system models. By designing the proper control gain parameters and quantizer accuracy, two sufficient conditions are established to guarantee the achievement of average consensus. Finally, two numerical simulations are provided to illustrate the effectiveness of theoretical results. Copyright © 2013 John Wiley & Sons, Ltd.     

A distributed algorithm for average consensus on strongly connected weighted digraphs

In this work we propose a distributed algorithm to solve the discrete-time average consensus problem on strongly connected weighted digraphs (SCWDs). The key idea is to couple the computation of the average with the estimation of the left eigenvector associated with the zero eigenvalue of the Laplacian matrix according to the protocol described in Qu et al. (2012). The major contribution is the removal of the requirement of the knowledge of the out-neighborhood of an agent, thus paving the way for a simple implementation based on a pure broadcast-based communication scheme.     

On average consensus in directed networks of agents with switching topology and time delay

In this article, the average consensus problem in directed networks of agents with both switching topology and coupling delay is investigated. First, based on a specific orthogonal transformation of the Laplacian matrix, an important proposition for verifying the positive definiteness of a class of quadratic forms is provided, which is of independent interest in matrix theory. And the relation between weakly connected and strongly connected digraphs is also investigated. Then, it is proved that all the agents reach the average consensus asymptotically for appropriate time delay if the communication topology keeps weakly connected and balanced. Finally, a numerical example is given to demonstrate the effectiveness and advantage of the new result.     

非平衡有向网络的完全分布式凸优化

分布式凸优化问题的目的是如何以分布式方法最小化局部智能体成本函数和,而现有分布式算法的控制步长选取依赖于系统智能体个数、伴随矩阵等全局性信息,有悖于分布式算法的初衷.针对此问题,提出一种基于非平衡有向网络的完全分布式凸优化算法(FDCOA).基于多智能体一致性理论和梯度跟踪技术,设计了一种非负余量迭代策略,使得FDCOA的控制步长收敛范围仅与智能体局部信息相关,进而实现控制步长的分布式设置.进一步分析了FDCOA在固定强连通和时变强连通网络情形下的收敛性.仿真结果表明本文构建的分布式控制步长选取方法对FDCOA在有向非平衡下的分布式凸优化问题是有效的.     

Consensus of second‐order discrete‐time multi‐agent systems with relative‐state‐dependent noises

This paper studies the consensus problem of second‐order discrete‐time multi‐agent systems with relative‐state‐dependent noises. Directed switching topologies are considered. Firstly, for a kind of switching topology with each digraph containing a spanning tree, we give a weak consensus result on the basis of the mode‐dependent average dwell time method. Then, if all digraphs in a switching topology are strongly connected and the corresponding Laplacian matrices have a common left eigenvector for zero eigenvalue, we prove that the mean square and almost sure consensus can always be guaranteed for an arbitrary switching sequence with some constant distributed control gains, and we also give the statistic properties of the final consensus points. Numerical examples are presented to illustrate the effectiveness of our results. Copyright © 2017 John Wiley & Sons, Ltd.     

Stochastic consensus of single‐integrator multi‐agent systems under relative state‐dependent measurement noises and time delays

This paper proposes a consensus algorithm for continuous‐time single‐integrator multi‐agent systems with relative state‐dependent measurement noises and time delays in directed fixed and switching topologies. Each agent's control input relies on its own information state and its neighbors' information states, which are delayed and corrupted by measurement noises whose intensities are considered a function of the agents' relative states. The time delays are considered time‐varying and uniform. For directed fixed topologies, condition to ensure mean square linear χ‐consensus (average consensus, respectively) are derived for digraphs having spanning tree (balanced digraphs having spanning tree, respectively). For directed switching topologies, conditions on both time delays and dwell time have been given to extend the mean square linear χ‐consensus (average consensus, respectively) of fixed topologies to switching topologies. Copyright © 2016 John Wiley & Sons, Ltd.     

基于事件触发的二阶多智能体系统平均一致性

针对二阶多智能体系统在固定无向拓扑下的平均一致性问题,为减少不必要的资源浪费,给出一种基于事件触发控制的一致性算法．首先,针对每个智能体设计基于状态误差形式的触发函数,只有当状态误差达到特定值时智能体才触发事件,在两个相邻事件触发时刻之间保持控制输入不变．然后,利用模型转换思想将系统的一致性问题转化为稳定性问题,并利用矩阵理论和李亚普诺夫理论给出系统达到平均一致的充分条件．最后,通过仿真实验验证该理论方案的有效性.     

Semi‐global output consensus of a group of linear systems in the presence of external disturbances and actuator saturation: An output regulation approach

This paper studies the problem of semi‐global leader‐following output consensus of a multi‐agent system. The output of each follower agent in the system, described by a same general linear system subject to external disturbances and actuator saturation, is to track the output of the leader, described by a linear system, which also generates disturbances as the exosystem does in the classical output regulation problem. Conditions on the agent dynamics are identified, under which a low‐gain feedback‐based linear state‐control algorithm is constructed for each follower agent such that the output consensus is achieved when the communication topology among the agents is a digraph containing no loop, and the leader is reachable from any follower agent. We also extend the results to the non‐identical disturbance case. In this case, conditions based on both the agent dynamics and the communication topology are identified, under which a low‐gain feedback‐based linear state‐control algorithm is constructed for each follower agent such that the leader‐following output consensus is achieved when the communication topology among the follower agents is a strongly connected and detailed balanced digraph, and the leader is a neighbor of at least one follower. In addition, under some further conditions on the agent dynamics, the control algorithm is adapted so as to achieve semi‐global leader‐following output consensus for a jointly connected undirected graph and the leader reachable from at least one follower. Copyright © 2015 John Wiley & Sons, Ltd.     

Necessary and sufficient conditions of stationary average consensus for second-order multi-agent systems

This paper investigates the stationary average consensus problem for second-order discrete-time multi-agent systems (SDMAS). A stationary consensus problem is to find a control algorithm that brings the state of a group of agents to a common constant value which is called the collective decision. We introduce the concept of stationary average consensus of SDMAS and propose a consensus algorithm. Based on the polynomial stability and the graph theory, we obtain two necessary and sufficient conditions of stationary average consensus of SDMAS. The last theorem provides an algebraic criterion of stationary average consensus, and can help us to determine the parameters in the consensus algorithm. Furthermore, in this consensus algorithm, only the states of the agents are transferred among the agents. Therefore, this algorithm can not only solve the stationary average consensus problem but also reduce the amount of transferred data. A numerical example is provided to illustrate the efficiency of our results.     

基于梯度估计的多智能体系统有限时间分布式优化

现有多智能体系统分布式优化算法大多具有渐近收敛速度,且要求系统的网络拓扑图为无向图或有向平衡图,在实际应用中具有一定的保守性.本文研究了具有强连通拓扑的多智能体系统有限时间分布式优化问题.首先,基于非光滑分析和Lyapunov稳定性理论设计了一个有限时间分布式梯度估计器.然后,基于该梯度估计器提出了一种适用于强连通有向图的有限时间分布式优化算法,实现了多智能体系统中智能体的状态在有限时间内一致收敛到全局最优状态值.与现有的有限时间分布式优化算法相比,新提出的有限时间优化算法适用于具有强连通拓扑的多智能体系统,放宽了系统对网络拓扑结构的要求.此外,本文基于Nussbaum函数方法对上述优化算法进行了拓展解决了含有未知高频增益符号的多智能体系统分布式优化问题.最后,通过仿真实例对提出的分布式优化算法的有效性进行了验证.