有向图中网络Euler-Lagrange系统的自适应协调跟踪

基于一致性理论, 在有向图中研究网络 Euler-Lagrange 系统的协调跟踪控制. 所有跟随智能体的动力学模型均为 Euler-Lagrange 方程. 在仅有部分跟随智能体能获取领航智能体信息的情形下, 同时考虑系统模型的参数不确定性, 设计分布式自适应控制律实现所有跟随智能体对领航智能体的跟踪. 针对领航智能体的运动状态, 考虑以下两种情形: 1) 领航智能体为固定点; 2) 领航智能体为动态点. 对第一种情形, 设计的控制律使得所有跟随智能体渐近交会于固定点; 对第二种情形, 首先对每个跟随智能体设计分布式连续估计器, 然后提出了分布式自适应控制律. 当每个跟随智能体均能获取领航智能体的加速度信息时, 设计的控制律能实现对领航智能体的渐近跟踪, 当跟随智能体不能获取领航智能体的加速度信息时, 跟踪误差是有界的. 最后通过仿真分析验证设计的控制算法是合理有效的.     

无需相对速度信息的多Euler-Lagrange 系统自适应神经网络包含控制

对含有模型非线性不确定性和外部扰动的多Euler-Lagrange 系统的分布式协调包含控制问题进行研究. 考虑通讯拓扑为有向图, 所有领航者均为动态, 且各智能体间相对速度信息不可测情况. 首先, 选取相对速度作为辅助变量, 引入低通滤波器进行估计; 然后, 采用神经网络方法逼近并补偿非线性不确定性, 提出一种分布式自适应包含控制律, 并应用Lyapunov 稳定性理论证明闭环系统的包含误差一致最终有界; 最后, 通过仿真算例验证了所提出的控制律的有效性.

     

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.     

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.     

有向图中模块化航天器系统相对轨道的自适应分布式一致性

基于多智能体系统一致性理论,对模块化航天器相对轨道的分布式一致性问题进行了研究.各模块之间的信息交互拓扑结构为更具一般性的有向图.当存在模块质量不确定性的情形下,设计了仅依赖模块自身及其邻近模块信息且无需模块间相对速度信息的自适应控制算法.针对模型中存在外部干扰的情形,通过引入带有时变自适应参数的变结构控制项,实现了对未知上界干扰的补偿,并且证明了闭环系统是渐近稳定的.此外,本文所设计的算法具有分布式的特点,不会因为模块数量的增多而增加所提算法的复杂度.最后对6个模块组成的模块化航天器的编队飞行进行了仿真分析,仿真结果表明本文设计的控制律是有效可行的.     

基于牵制控制的异质多智能体系统的群一致性研究

为了研究由线性的一阶智能体、二阶智能体和非线性的EL （Euler-Lagrange）结构智能体组成的异质多智能体系统的群一致性,并实现同一个子群中智能体状态趋于期望的状态,针对无向的固定拓扑情况,提出了基于牵制控制的分布式控制协议。并通过代数图论、李雅普诺夫函数和拉塞尔不变集原理证明了控制协议的可行性。数值仿真结果表明:在所提控制协议作用下能够实现包含非线性EL结构的异质多智能体系统的群一致性,与未引入牵制控制的群一致性算法相比各个子群能够趋于期望的状态。     

基于记忆状态的多智能体系统快速分组一致性

针对拓扑结构为有向图的一阶多智能体系统,研究在组间状态差值事先未知以及状态差值事先已知两种情况下的系统快速分组一致性问题.设计基于智能体记忆状态的快速一致性协议,利用矩阵理论和频域分析法分别给出两种情况下系统收敛一致的充分条件,同时给出使系统能够更快收敛的记忆状态选取时间上界.通过仿真实验验证了所提出协议的正确性.     

基于局部控制器的非线性多智能体一致性分析

研究非线性多智能体系统的一致性问题,由于多智能体要求在网络中所有个体状态趋于一致,所以采用有向图表示的多智能体系统的拓扑结构形式.为了验证一致性,提出一类由自反馈控制器和协调控制器构成的局部控制器,由自反馈控制器保证每个动态节点的稳定性,协调控制器保证网络的全局稳定性和信息的正常交流.根据Lapunov稳定性理论,利用线性化方法,分别采用非线性多智能体系统在固定和切换网络拓扑中进行一致性实验.最后采用6个非线性智能体组成的网络拓扑结构进行计算机仿真,结果验证了理论的正确性.     

牵制控制下的多智能体系统群一致性

本文研究了一类多智能体系统在牵制控制下的群一致性问题,提出了融合群内信息交互、群间信息交互和牵制控制器的一致性协议.对固定拓扑下的二群组智能体系统和切换拓扑下的多群组智能体系统,利用稳定性理论和图论分别给出了适用于任意拓扑结构的充要条件,使得智能体系统在所提协议和牵制控制器的联合作用下实现预期的群一致.针对拓扑图中含有生成树这一特例,分析了被施加牵制控制的智能体在结构中的具体位置.此外,对切换拓扑下进行非线性交互的多群组智能体系统,利用Lyapunov方法推导出一充分条件,得出只要对多智能体系统的一部分主体进行牵制控制,则所有智能体即可在所提协议和牵制控制器的作用下渐近收敛于各自的期望一致平衡点.最后,仿真例子验证了所提方法的有效性.     

多智能体系统基于自适应控制下的二分-分量一致性

二分-分量一致性是指网络系统中部分具有相似特性智能体的某些分量随时间推移趋于相同的值,而剩余智能体的某些分量则随时间趋于相反的值,是一种弱于恒同一致和二分一致的动力学行为.为此,对符号网络上非线性多智能体系统的二分-分量一致性问题展开研究.首先,针对多智能体系统中各智能体之间存在的合作关系或竞争关系,设计有效的自适应牵制控制器;随后,基于Lyapunov稳定性理论和矩阵理论,导出该非线性系统二分-分量一致性得以实现的充分条件;最后,通过数值模拟验证理论结果.     

Distributed containment control for Lagrangian networks with parametric uncertainties under a directed graph

In this paper, we study the distributed containment control problem for networked Lagrangian systems with multiple dynamic leaders in the presence of parametric uncertainties under a directed graph that characterizes the interaction among the leaders and the followers. We propose a distributed adaptive control algorithm combined with distributed sliding-mode estimators. A necessary and sufficient condition on the directed graph is presented such that all followers converge to the dynamic convex hull spanned by the dynamic leaders asymptotically. As a byproduct, we show a necessary and sufficient condition on leaderless consensus for networked Lagrangian systems under a directed graph. Numerical simulation results are given to show the effectiveness of the proposed control algorithms.     

Cooperative tracking control for general linear multiagent systems with directed intermittent communications: An artificial delay approach

This paper investigates the consensus tracking problem for general linear multiagent systems on directed graph containing a spanning tree. For the considered linear systems, the consensus tracking aim cannot be achieved by using only memoryless static relative output feedbacks. Of particular interest is that both current and delayed relative output information of agents are required to achieve consensus. For the case of continuous communication among agents, an artificial delay output feedback control method is proposed. By utilizing the Taylor representation for the delayed signal with the remainder in the integral form, a delay‐dependent sufficient condition is presented to guarantee the exponential convergence of the global tracking error systems. For the intermittent case, the consensus tracking performance can still be guaranteed based on a multiple graph‐dependent Lyapunov functionals method. It is theoretically revealed that the time delay plays a key role in the exponential convergence of the closed‐loop systems, and the definite relationships among the time delay, network structure, communication rate, and consensus convergence rate are also provided. The effectiveness of the proposed control scheme is confirmed by numerical simulations.     

无速度输入多智能体系统的一致性

本文研究了有无引导者的多智能体系统在非线性协议下的一致性问题.当智能体速度信息无法获知时,分别针对有无引导者的多智能体系统设计了包含辅助系统和智能体相对位移信息的非线性分布式协议.借助图论、Lyapunov稳定性理论、Barbalat引理等方法,推导出有无引导者的多智能体系统在连通无向通讯网络中实现一致的充分条件,其次,设计了一种新的能使引导–追随者多智能体系统在有向通讯网络中实现期望一致的协议.最后,数值仿真验证了结果的正确性.     

基于事件驱动的多智能体有限时间分群一致控制

针对二阶线性多智能体系统的分群一致控制问题,考虑智能体通信拓扑同时包含协作和对抗关系,提出一种基于事件驱动控制的有限时间分布式领航跟随分群一致性算法,该算法可使多智能体系统在有限时间内实现分群一致,即各子组内的智能体实现状态一致,不同子组收敛至不同一致状态.采用事件驱动控制机制,设计事件驱动函数及事件触发条件,降低智能体控制器更新频率,减少系统能耗.基于代数图论和李雅普诺夫稳定性理论推导出系统的有限时间稳定性条件,通过巧妙构造Lyapunov函数,给出系统有限收敛时间的显式估计,同时证明在所提出的事件驱动机制下,每个智能体相邻触发时间间隔有严格的正下界,即避免了芝诺行为.仿真实验验证了所提出的有限时间事件驱动分群一致控制算法的有效性.     

Bipartite tracking of homogeneous and heterogeneous linear multi-agent systems

In this paper, we consider bipartite tracking of linear multi-agent systems with a leader. Both homogeneous and heterogeneous systems are investigated. The communication between agents is modelled by a directed signed graph, where the negative (positive) edges represent the antagonistic (cooperative) interactions among agents. Linear Quadratic Regulator (LQR)-based approach is used to derive the distributed protocol for the follower agent to achieve bipartite tracking of the leader. It is shown that solving the bipartite tracking problem over the structurally balanced signed graph is equivalent to solving the cooperative tracking problem over a corresponding graph with nonnegative edge weights. This bridges the gap between the newly raised bipartite tracking problem and the well-studied cooperative tracking problem. Three novel control protocols are proposed for both cooperative and bipartite output tracking of heterogeneous linear multi-agent systems. Numerical examples are given to show the effectiveness of our control protocols.     

Joining consensus of networked multi-agent systems with nonlinear couplings and weighting constraints

This paper studies the joining consensus of networked multi-agent systems subject to nonlinear couplings and weighted directed graphs via pinning control. A weighted-average consensus protocol is proposed to achieve the collective decision by interacting with the local information of some pinned agents. By proposing a novel joining consensus protocol, average consensus and general consensus strategies are joined to achieve an agreement for the weighting networked system. Furthermore, by calculating a proper consensus gain and using finite control Lyapunov controllers, an efficient joining consensus protocol is presented to improve the consensus speed. Sufficient conditions for achieving the consensuses asymptotically are proved. Finally, theoretical results are validated via simulations.     

Average Convergence for Directed & Undirected Graphs in Distributed Systems

Consensus control of multi-agent systems is an innovative paradigm for the development of intelligent distributed systems. This has fascinated numerous scientific groups for their promising applications as they have the freedom to achieve their local and global goals and make their own decisions. Network communication topologies based on graph and matrix theory are widely used in a various real-time applications ranging from software agents to robotics. Therefore, while sustaining the significance of both directed and undirected graphs, this research emphases on the demonstration of a distributed average consensus algorithm. It uses the harmonic mean in the domain of multi-agent systems with directed and undirected graphs under static topologies based on a control input scheme. The proposed agreement protocol focuses on achieving a constant consensus on directional and undirected graphs using the exchange of information between neighbors to update their status values and to be able to calculate the total number of agents that contribute to the communication network at the same time. The proposed method is implemented for the identical networks that are considered under the directional and non-directional communication links. Two different scenarios are simulated and it is concluded that the undirected approach has an advantage over directed graph communication in terms of processing time and the total number of iterations required to achieve convergence. The same network parameters are introduced for both orientations of the communication graphs. In addition, the results of the simulation and the calculation of various matrices are provided at the end to validate the effectiveness of the proposed algorithm to achieve consensus.     

Flocking of multi‐agent nonholonomic systems with unknown leader dynamics and relative measurements

In this paper, we consider the distributed flocking control problem of multi‐agent nonholonomic systems with a virtual leader whose dynamics is unknown; state information is time varying and not available to all agents under both fixed and switching topologies. On the basis of the relative velocity and orientation information of neighboring agents, two distributed discontinuous control protocols are designed for fixed and switching topologies, respectively. By using tools from algebraic graph theory and nonsmooth analysis, the proposed distributed discontinuous control protocols guarantee that the velocities and orientations of the agents exponentially converge to the velocity and orientation of the virtual leader, respectively, while ensuring collision avoidance of the whole group, if the interaction graph among agents is undirected and the virtual leader with bounded time‐varying velocity has directed paths to other agents. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.