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。     

组合控制协议增强多智能体系统一致性

针对离散时间下基于切换拓扑多智能体系统一致性问题,设计出一种基于约束集虚拟邻居选取分布式一致性协议。该协议中,智能体采用通信扇区机制构造出虚拟邻居作为控制协议输入进行状态演化,并设计智能体调整因子的取值方式。在此基础上,智能体通过约束集保持初始通信拓扑的连接边来保证系统的连通性。最后,理论分析与大量仿真实例结合,与经典模型进行比较,验证了新的一致性协议的有效性,表明其可增强系统一致性,减少系统收敛的簇,并提高系统的一致性收敛速度。     

基于事件触发机制的多智能体网络平均一致性研究

文章研究了事件触发机制下具有固定和切换拓扑结构的多智能体网络的平均一致性问题。为了有效降低多智能体一致性控制协议的更新次数,文章提出了仅依赖于各智能体及其邻居节点信息的分布式事件触发机制。为了使多智能体网络渐近收敛至初始平均状态,文章提出了基于事件触发机制的多智能体平均一致性协议。然后,文章建立了事件触发机制下的闭环系统模型,并分别获得了固定和切换拓扑结构下多智能体网络平均一致收敛的充分条件。仿真表明,基于事件触发机制的平均一致性协议保证了多智能体网络的平均一致性,并且分布式事件触发机制有效降低了多智能体一致性协议更新次数。     

基于影响力网络模型的多智能体一致性协议

如何增强系统一致性是多智能体系统研究中的一个重要问题。传统一致性协议通常未考虑拓扑中的关键节点,并且拓扑权重单一,从而导致系统更容易分裂。基于人际关系网络中的关键人物可以促进不同社区信息交流的思想,提出了一种影响力网络模型（influence network model,INM）。首先,提出了分布式的Hub Node识别算法（distributed hub node identify algorithm,DHNI）,用于区分关键节点和非关键节点,可以应用在分布式多智能体系统中。其次,提出了基于分布式hub node的拓扑权重设计算法（distributed hub node-based topology reweighting algorithm,DHNTR）,量化不同节点对其邻居的影响力。最后提出了基于影响力网络的一致性协议。设计了公共Lyapunov函数,分析了系统的全局稳定性,证明了系统具有Lyapunov意义下的稳定性。仿真实验表明该协议可以增强系统一致性。     

脉冲控制下基于合作机制的多智能体系统分组一致性研究

针对在脉冲控制下非线性多智能体系统的分组一致性协同控制问题,本文基于复杂系统中智能体间的合作机制,提出了一种新颖的具有领导-跟随网络的分组一致性控制协议.该协议控制智能体仅在脉冲时刻接收来自邻居节点的信息并更新自己的状态,减少智能体因持续接收邻居信息更新自己状态而造成的网络开销.针对不同组之间智能体的信息交互,该协议具有防止组间干扰的机制,降低了不同组之间的通信干扰,提高系统鲁棒性.此外,本文还介绍了一种适用于非线性系统的方案,增强协议的适应性.基于实现分组一致性条件,构建了多智能体系统的动力学模型,并进行了协议的详细设计和理论推导.最后,通过仿真验证了协议的正确性和有效性.     

多智能体系统初始状态一致性应用研究

针对一阶多智能体系统,研究了含有时滞和不含时滞两种情形下收敛到初始状态（认为初始状态都为0）的问题,提出了一种使多智能体系统能够收敛到初始状态的一致性协议。在此一致性协议的基础上,严格推导了该多智能体系统达到初始状态的充分性判据。结合无人机编队中的应用,给出了两种情况下多智能体系统收敛到初始状态的仿真,验证了所提出的一致性协议的正确性以及充分性判据的有效性。     

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.     

2阶多智能体网络在切换拓扑下的群一致性

针对2阶多智能体网络的群一致性问题,提出了基于牵引控制方法的群一致性协议.考虑到网络模型具有切换拓扑结构,在模型中引入相应的虚拟领导者.对于网络中的每一个智能体,其一致性协议依赖于智能体邻居的状态及速度信息,并受到虚拟领导者的牵引控制;进一步地,来自虚拟领导者的牵引控制可以随时间发生变换.利用代数图论、线性矩阵不等式和李亚普诺夫稳定性理论,对网络进行群一致性分析,给出了切换拓扑下2阶多智能体网络达到群一致性的充分条件.最后,数值仿真验证了理论结果的有效性.     

基于模型参考的异构多智能体平均一致性

针对参数未知的异构线性多智能体系统，在无向或平衡有向网络下提出一种固定输出平均一致性协议，使得每个智能体的输出达到它们初始输出的平均值。首先，网络中每个智能体都被建模成阶数不同且相关度为1或2的未知线性系统，并根据自身及其邻居节点的输出更新其状态；其次，基于模型参考控制方法，对不同相关度的智能体定义相对应的模型；最后，提出一致性协议使每个智能体的输出收敛至其参考模型的输出，即达到固定输出平均一致。仿真实验利用了一个说明性的例子验证了所提协议的有效性和收敛性。     

线性多智能体系统一致性问题的部分稳定性方法

提出了处理高阶线性多智能体系统一致性问题的线性变换.该线性变换将一致性问题转化为一个部分稳定问题.研究了一般线性协议下线性多智能体系统的三个问题: 1) 寻找一致性收敛判据; 2) 计算一致性函数; 3) 设计线性一致性协议的增益矩阵.具体来说,提出了基于矩阵 Hurwitz 稳定的一致性收敛的充分必要条件,给出了一致性函数的解析表达式,同时建立了一致性协议的增益矩阵与多智能体系统收敛时间和一致性精度的关系,并针对预先给定的收敛时间和精度要求设计了增益矩阵.     

Interval consensus problem of multi-agent systems in accordance with switching protocol

In this paper, we discuss the interval consensus problem of multi-agent systems by providing a special Laplacian of directed graphs. As one of the most important issues in the coordination control of multi-agent systems, the consensus problem requires that the output of several spatially distributed agents reach a common value that depends on the states of all agents. For the given consensus protocol and initial states, a fixed consensus value is obtained. The resulting consensus value, however, may not be ideal or meet the quality that we require from the multi-agent system. In this paper, by introducing two state-dependent switching parameters into the consensus protocol, the system given by the proposed protocol can globally asymptotically converge to a designated point on a special closed and bounded interval. In other words, the system given by the proposed protocol can globally asymptotically reach interval consensus and then the system can also achieve a generalised interval average consensus if the directed graph is balanced. Simulations are presented to demonstrate the effectiveness of our theoretical results.     

Reaching a consensus: a discrete nonlinear time-varying case

In this paper, we have considered a nonlinear protocol for a structured time-varying and synchronous multi-agent system. By means of cubic triple stochastic matrices, we present an opinion sharing dynamics of the multi-agent system as a trajectory of a non-homogeneous system of cubic triple stochastic matrices. We show that the multi-agent system eventually reaches to a consensus if either of the following two conditions is satisfied: (1) every member of the group people has a positive subjective distribution on the given task after some revision steps or (2) all entries of some cubic triple stochastic matrix are positive.     

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.     

Outdoor cooperative flight using decentralized consensus algorithm and a guaranteed real-time communication protocol

This paper describes the implementation of a decentralized consensus law with theoretically provable convergence properties on a multi-agent testbed comprising of quadrotors. It is shown that for small roll and pitch angles and well-tuned control loops, the quadrotor dynamics can be approximated as a pair of double integrators. Several experiments are carried out in an outdoor environment for validation of the consensus law which is based on double integrator dynamics. For any arbitrary initial positions of the quadrotors, the consensus law is able to drive them to an autonomously decided common point, given that the communication graph is connected at each instant of time. The resulting experimental trajectories and the consensus point matches with theoretical predictions. For guaranteeing real-time reliability required for such coordinated motion, a novel synchronized, time-slotted, scalable and fully airborne communication protocol is proposed. The protocol avoids data collisions and ensures real-time, reliable communication between agents. It can also address changing communication graph topologies, temporary link-breaks and additions. Using this underlying protocol, the quadrotors attain consensus for static and dynamic communication graphs. Experiments to observe the effect of communication rate on consensus performance are also conducted.     

带有不连续动力学的非线性多智能体系统固定时间一致性EI北大核心CSCD

本文研究了一类带有不连续动力学和有界扰动的非线性多智能体系统领导跟随固定时间一致性问题.首先,在不对称的有向拓扑图下,本文设计了一种辅助信号,该辅助信号用于观测领导者状态,且该辅助信号不在通信信道中传输,可以有效地减少系统计算代价.随后,基于辅助信号,本文设计了一种不连续控制协议,以实现多智能体系统固定时间收敛.然后,利用非光滑分析、Lyapunov稳定性理论及代数图论等证明系统可在任意初始状态下达到固定时间一致.最后,仿真实例进一步验证了理论结果的有效性.     

Second-order consensus in multi-agent systems based on second-order neighbours’ information

This paper mainly investigates the consensus of second-order multi-agent systems by using the second-order neighbours’ information. The comparison between the convergence rate of second-order neighbour protocol and the one of general protocol is developed. When multi-agent system achieves maximum speed consensus, the relation between the parameter in general protocol and that in second-order neighbour protocol is analysed. If there exists delay in communication, the delay margins of general protocol and second-order neighbour protocol are derived. Numerical examples are given to illustrate the effectiveness of the proposed methods.     

Consensus control of leader-following nonlinear multi-agent systems with distributed adaptive iterative learning control

This paper addresses the consensus problem of leader-following nonlinear multi-agent systems with iterative learning control. The assumption that only a small portion of following agents can receive the information of leader agent is considered. To approximate the nonlinear dynamics of a given system, the radial basis function neural network is introduced. Then, a distributed adaptive iterative learning control protocol with an auxiliary control term is designed, where the estimates of nonlinear dynamics are applied in control protocol design and three adaptive laws are presented. Furthermore, the convergence of the proposed control protocol is analysed by Lyapunov stability theory. Finally, a simulation example is provided to demonstrate the validity of theoretical results.     

Solving a modified consensus problem of linear multi-agent systems

A distributed protocol is proposed for a modified consensus problem of a network of agents that have the same continuous-time linear dynamics. Each agent estimates its own state using its output information and then sends the estimated state to its neighbor agents for the purpose of reaching a consensus. The modified consensus problem requires the group decision value to be a linear function of initial states and initial estimated states of all agents in the network, and the transformation matrix associated with this linear function not to be a zero matrix. It is proved that under the proposed control protocol, the modified consensus problem can be solved if and only if the system matrices of the agent’s dynamics are stabilizable and detectable, the input matrix is not a zero matrix, and the communication topology graph has a spanning tree. The proposed protocol can also be extended to multi-agent systems where agents are described by discrete-time linear dynamics. The corresponding necessary and sufficient conditions are provided as well.