基于事件触发的拓扑切换异构多智能体协同输出调节

研究切换拓扑下线性异构多智能体系统的协同输出调节问题,并设计了一个基于事件触发的输出调节控制机制.设计的控制机制不仅可以实现智能体对外部系统的渐近跟踪和干扰抑制,还可以有效减少智能体之间的信息传递数量,从而降低通信负载减少网络能耗.最后通过仿真验证结论的有效性.     

网络化热方程的集中事件触发控制

本文对热方程建模的分布式参数化多智能体系统进行研究,设计了基于事件触发控制下的一致性边界控制器,将网络化热方程的状态驱动到相同的稳定状态.其中每一个子系统的边界信息能被测量,并且所有的智能体由无向静态拓扑连接.事件触发控制器由以下两部分组成:一是基于网络拓扑的边界局部交互作用,驱动所有子系统达到相同的状态;二是由事件触发条件建立的触发时刻.本文证明了在事件触发的边界一致性控制下两个连续触发时刻之间存在最小停留时间以避免Zeno现象;同时利用李雅普诺夫函数分析并保证了闭环系统的稳定性和适定性.最后,给出了由5个热方程组成的多智能体系统的仿真算例,结果证实了本文所设计事件触发控制器的真实性.     

基于事件触发的非线性多智能体系统的固定时间分群一致性

结合事件触发控制方法研究非线性多智能体系统的固定时间分群一致性问题.提出一种非线性分布式事件触发分群一致性控制协议,并给出状态信息触发控制器更新的条件.该控制协议不受入度平衡条件限制,且只需自身状态信息与邻居智能体进行通信即可在固定时间内快速实现分群一致性.系统收敛时间与智能体的初始状态无关,可有效降低系统控制器更新频率和系统的资源消耗.结合代数图论、矩阵分析及Lyapunov稳定性理论,证明在所提出协议作用下,多智能体系统在固定时间内能够实现分群一致性,且不存在Zeno行为.最后,通过仿真实例检验了理论结果的可行性.     

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.     

带输出死区的多智能体系统预设时间事件触发式协同控制

针对带有输出死区的多智能体系统的一致性控制问题,提出一种可预设时间的事件触发式协同控制方法.输出死区现象普遍存在于实际系统,对控制回路中负反馈调节影响较大,会导致系统控制性能的下降.为此,通过结合Nussbaum函数对输出死区特性进行补偿,以削弱其对系统性能的影响,但上述问题解决的同时也会加剧对系统控制传输资源的占用.由于多智能体系统依靠智能体之间频繁的信息交互实现控制目标,自身传输资源有限.考虑到实际系统的限制,利用事件触发控制策略节省系统的控制传输资源.更进一步,为有效提高系统性能,使系统能够快速达到稳定,引入一类转换函数进行系统变换,实现系统同步误差在预设时间内收敛于紧集的目标.理论分析和仿真结果验证了所提出方法的有效性.     

状态时延和全状态约束下的多智能体系统自适应事件触发控制

研究有向通信图下非线性多智能体系统的一致控制问题.首先,通过引入性能函数,使输出误差满足预定性能;其次,采用障碍Lyapunov函数,保证所有状态满足约束条件,结合李雅普诺夫-克拉索夫斯基(LyapunovKrasovskii, LK)泛函和杨氏不等式消除状态时延的影响,利用径向基函数神经网络(radial basis function neural networks, RBF NNs)逼近未知非线性函数;再次,设计自适应事件触发控制器,实现所有智能体的输出一致性,并基于Lyapunov稳定性理论证明闭环系统半全局有界稳定;最后,通过对比仿真验证所设计控制策略的有效性.     

单向通信拓扑领航者动态未知线性多智能体系统的协同迭代学习控制

研究单向通信拓扑领航者动态未知线性多智能体系统的协同跟踪问题.基于邻居的相对状态信息,设计了分布式迭代学习控制律实现对领航者的协同跟踪控制,采用Lyapunov-Krasovskii函数分析闭环系统的稳定性与收敛性.进而,将状态反馈结论拓展到输出反馈,通过构造局部观测器估计不可量测的状态信息,采用估计的相对状态信息设计了分布式迭代学习控制器.对于以上两种情形,多智能体系统在通讯拓扑含有生成树的条件下能够实现与领航者的状态同步,同时,所设计的分布式迭代学习律能够对领航者未知输入进行精确估计.仿真实例验证了所提方法的有效性.     

具有容性负载的直流微电网系统分布式协同控制

针对一类具有容性负载的直流微电网系统, 提出了分布式协同控制方法. 具有容性负载的直流微电网是一类耦合动态互联非线性网络化系统, 可将DC-DC变换器在信息层视为智能体, 在每个子系统模块中, 引入容性负载电压观测器, 耦合并联非线性系统负载均衡控制设计问题可解耦成一阶积分器多智能体系统的输出一致性跟踪问题. 基于最近邻原则, 通过在控制器中引入比例、积分环节, 设计了增益可调的分布式协同PI控制律, 当有向图满足至少含有一棵生成树的条件下, 通过子系统间的局部交互, 可以实现负载均衡的目标. 通过分析增广系统矩阵的特征值证明了整个闭环系统的稳定性. 仿真和实验说明了所提出的控制方法的有效性及可行性.     

多智能体网络系统的自适应协调控制

为实现多智能体网络系统的协调控制,设计了一种新型的带有自适应协调器的控制器.基于动态图建立了多智能体网络系统的模型,并考虑了系统的非线性互联和不可避免存在的时变时滞.应用分布式控制策略,设计了自适应参数估计的协调器,用于调节智能体之间的互联强度,使网络达到稳定的预设水平.并基于Lyapunov-Kra-sovskii泛函和自适应动态偏差反馈控制技术,根据拉萨尔不变集原理证明了偏差控制系统的渐近收敛性.这种控制方法,可在系统参数不确定的情况下,同时完成参数估计和协调控制.所设计的控制律和自适应律简单,易于实现,仿真示例验证了所提方法的有效性.     

考虑状态受限和一致性的微电网二次控制

为解决交流微电网下垂控制产生的偏差问题, 本文采用二次控制对分布式电源输出电压和频率进行调节. 将微电网看成分布式多智能体系统, 智能体间通过稀疏网络进行通信, 运用多智能体一致性协议, 本文提出一种基 于障碍Lyapunov函数和自适应模糊系统的二次电压和频率控制器. 采用障碍Lyapunov函数设计控制器, 不但能保 持系统的稳定性, 还可使输出的电压和频率限制在预设的范围内. 采用自适应模糊系统可对系统中的一些参变量的 变化进行估计, 提高了控制器的鲁棒性. 本文给出了严格的稳定性证明. 通过对负载变化, 以及拓扑结构改变等的 仿真测试, 验证了所提方案的有效性.     

Cooperative output regulation of heterogeneous multi-agent systems based on passivity

This paper investigates the problem of cooperative output regulation of heterogeneous linear multi-agent systems. A passive framework is presented for the stabilisation analysis of cooperative output regulation, which can overcome the difficulty caused by the fact that the global dynamics of heterogeneous multi-agent systems depends on the global communication structure. An adaptive distributed observer is proposed to estimate the state of the exosystem, and the proposed distributed observer is independent of any global information of the communication graph. Based on passivity design and adaptive distributed observer, both a distributed state feedback and a distributed output feedback protocol are designed for output synchronisation of heterogeneous multi-agent systems. The gain matrices of the distributed protocols and observers are obtained by a Riccati equation design approach. Furthermore, sufficient local conditions for solving the problem of cooperative output regulation of heterogeneous multi-agent systems are presented. Finally, numerical simulation results are given to illustrate the effectiveness of the proposed distributed control schemes.     

Cooperative output regulation of multi-agent systems with switched leader dynamics

In this paper, the cooperative output regulation problem for heterogeneous multi-agent systems is addressed by considering a switched leader dynamics. The switched leader dynamics consists of multiple linear models and a switching rule governing the switches among them. A switched leader is capable of generating various sophisticated reference signals for more complicated multi-agent coordination tasks. A novel distributed hybrid impulsive switching control scheme is proposed to achieve cooperative output regulation. Distributed switching stability is established using the average dwell-time technique with multiple Lyapunov functions. Moreover, the associated distributed control synthesis conditions are formulated in terms of linear matrix inequalities plus linear matrix equations. As a result, both switching rules for the leader and distributed switching protocols for the followers can be jointly synthesised via efficient semi-definite programming. An example has been used to demonstrate the effectiveness of the proposed approach.     

DoS攻击下具备隐私保护的多智能体系统均值趋同控制

均值趋同是一种广泛应用于分布式计算和控制的算法, 旨在系统通过相邻节点间信息交互、更新, 最终促使系统中所有节点以它们初始值的均值达成一致. 研究拒绝服务(Denial-of-service, DoS)攻击下的分布式离散时间多智能体系统均值趋同问题. 首先, 给出一种基于状态分解思想的分布式网络节点状态信息处理机制, 可保证系统中所有节点输出值的隐私. 然后, 利用分解后的节点状态值及分析给出的网络通信拓扑条件, 提出一种适用于无向通信拓扑的多智能体系统均值趋同控制方法. 理论分析表明, 该方法能够有效抵御DoS攻击的影响, 且实现系统输出值均值趋同. 最后, 通过仿真实例验证了该方法的有效性.     

Distributed cooperative stabilisation of continuous-time uncertain nonlinear multi-agent systems

This paper addresses the distributed cooperative stabilisation problem of continuous-time uncertain nonlinear multi-agent systems. By approximating the uncertain dynamics using neural networks, a distributed adaptive cooperative controller, based on the state information of the neighbouring agents, is proposed. The control design is developed for any undirected connected communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case. An observer-based distributed cooperative controller is devised and a parameter dependent Riccati inequality is employed to prove stability of the overall multi-agent systems. This design is less complex than the other design methods and has a favourable decouple property between the observer design and the controller design for uncertain nonlinear multi-agent systems. For both cases, the developed controllers guarantee that all signals in the closed-loop network are uniformly ultimately bounded, and the states of all agents cooperatively converge to a small neighbourhood of origin. A comparative study is given to show the efficacy of the proposed method.     

A self-tuning adaptive distributed observer approach to the cooperative output regulation problem for networked multi-agent systems

In this paper, we first propose a self-tuning distributed observer for a multi-agent system, which is capable of providing the estimation of the leader's signal to various followers without assuming all the followers know the system matrix of the leader. We then further develop a novel adaptive distributed control law to solve the cooperative output regulation problem for linear heterogeneous multi-agent systems. This control law offers two advantages in that it makes less use of the information of the network as well as the information of the leader and external disturbances, and it avoids calculating the observer gain.     

Distributed output regulation for linear multi-agent systems with communication delays

In this paper, a distributed output regulation approach is presented for the cooperative control of linear multi-agent systems in the presence of communication delays. Both dynamic state and output feedback control laws are designed for achieving the property of output regulation. Sufficient conditions for the existence of these control laws are provided in terms of linear matrix inequalities. Simulation results are given to support the efficiency of the proposed distributed output regulation approach.     

Composite nonlinear feedback control for cooperative output regulation of linear multi-agent systems by a distributed dynamic compensator

This paper investigates the cooperative output regulation problem of linear multi-agent systems with a linear exogenous system (exo-system). The network topology is described by a directed graph which contains a directed spanning tree with the exo-system as the root. Aiming at improving the transient performance of the multi-agent systems, a dynamic control law is developed by the composite nonlinear feedback (CNF) control technique. In particular, a distributed dynamic compensator independent of the interaction on the compensator states of agents among the network, is adopted. The solvability condition for the cooperative output regulation problem is obtained using the small-gain theory, which will not be destroyed by adding the nonlinear feedback part of the CNF control law. It is also shown that in the case with the exo-system not diverging exponentially, the small-gain condition can be guaranteed using the low-gain design. Finally, simulation results illustrate that the proposed CNF control law improves the transient performance for the cooperative output regulation of linear multi-agent systems.     

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.     

Containment control of a class of heterogeneous nonlinear multi-agent systems

This paper studies the containment control of a class of heterogeneous nonlinear multi-agent systems under general directed graph. Every follower agent is a nonlinear system in the output feedback form with the same relative degree. The authors’ goal is to design a distributed dynamic controller such that the outputs of followers enter the convex hull spanned by the outputs of leaders. To this end, the containment problem is converted into a cooperative output regulation problem, a distributed adaptive recursive procedure and the internal model are employed to design the distributed controller.     

Robust cooperative control for multi-agent systems via distributed output regulation

Robust cooperative control for multi-agent systems is considered in this paper, under the framework of the distributed output regulation problem. With some fundamental assumptions, two necessary and sufficient conditions are given for the distributed output regulation problem to be solvable. The algorithm of designing the robust distributed control law is provided, with the help of internal models. It is shown that this robust controller is effective in a neighborhood of the nominal system, which is tolerant of system uncertainties.