Bipartite Byzantine-resilient event-triggered consensus control of heterogeneous multi-agent systems

This article studies the bipartite resilient event-triggered consensus control for a class of the heterogeneous multi-agent systems. Due to the external cyberattacks, some agents may become the Byzantine agents and will affect the behavior of the other agents. To improve the security of the multi-agent systems against the Byzantine agents, a novel bipartite event-triggered heterogeneous mean-subsequence-reduced algorithm is designed. First, to handle the heterogeneous multi-agent systems, a state transformation is carefully designed, to facilitate the design and analysis of the bipartite resilient consensus algorithm. Based upon the designed state transformation, the bipartite resilient control inputs are constructed, where the structural balance analysis shows that the resulting effective signed graph and the equivalent signed graph are both structurally balanced, if the signed graph of the multi-agent systems is structurally balanced. In addition, a dynamic event-triggered mechanism is proposed, where a set of dynamic factors are introduced into the event-triggered functions to prevent the usage of the global topology information. By virtue of the designed algorithm, it is guaranteed that the heterogeneous multi-agent systems can achieve the bipartite consensus in the presence of the Byzantine agents, and the communication burden among the agents can be reduced. The numerical simulations are conducted to verify the effectiveness of the proposed algorithm.     

Semi-global weighted output average tracking of discrete-time heterogeneousmulti-agent systems subject to input saturation and external disturbances

In this paper, we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances. The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents. We design both the state feedback and output feedback control protocols for each follower agent. In particular, a distributed state observer is designed for each follower agent that estimates the state of each leader agent. In the output feedback case, state observer is also designed for each follower agent to estimate its own state. With these estimates, we design low gain-based distributed control protocols, parameterized in a scalar low gain parameter. It is shown that, for any bounded set of the initial conditions, these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small. Simulation results illustrate the validity of the theoretical results.     

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.     

异质多智能体系统二分一致性的充要条件

针对由一阶智能体和二阶智能体组成的异质多智能体系统的二分一致性问题,对连续和离散系统情形分别设计了二分一致性协议。基于结构平衡的拓扑,通过规范变换实现了从具有敌对关系的系统到具有非负连接权重系统的转化,将二分一致性问题转变为一般一致性问题。进一步,运用代数图论和矩阵理论分析闭环控制系统的动态特性,得到了异质多智能体系统渐近实现二分一致性的充要条件。最后通过数值模拟验证了所得结果的有效性。     

符号网络下一类非线性二分一致性系统的跟踪控制

研究具有对抗交互的一类非线性多智能体系统的二分一致性跟踪控制问题,借助有向符号图刻画智能体之间的通信关系,并假定符号图是结构平衡的.进一步,借助符号图网络对二分一致性跟踪问题进行公式化描述.基于最近邻原则,结合拉普拉斯矩阵、牵制矩阵、符号函数、耦合增益参数等,设计分布式控制律.利用Barbalat引理和李亚谱诺夫函数证明整个闭环系统的渐近稳定性,在保持闭环系统稳定的条件下推导出耦合增益的下界.最后通过仿真验证所提出方法的有效性.     

Bipartite output synchronization of heterogeneous multiagent systems on signed digraphs

This paper studies the bipartite output synchronization problem of general linear heterogeneous multiagent systems on signed digraphs. We first show that, for heterogeneous multiagent systems, the bipartite output synchronization over the structurally balanced signed digraphs and the conventional output synchronization over the associated nonnegative digraphs are equivalent. Then, 3 different control protocols, using full‐state feedback, static output feedback, and dynamic output feedback are designed at each agent to solve the bipartite output synchronization problem based on solutions to the corresponding output regulator equations. Explicit local design procedures are proposed for all 3 control protocols. The compensators employed in these protocols incorporate only one copy of the virtual exosystem's dynamics, regardless of the dimensions of the outputs. This results in lower‐dimensional compensators and controllers and, hence, is more computationally tractable compared to the popular internal model principle‐based control protocols. Numerical simulations over 3 different signed communication digraphs validate the proposed control protocols.     

对抗网络下时滞非线性多智能体系统固定时间二分一致性

本文针对一类存在输入时延的非线性多智能体系统,研究了其在结构平衡的无向符号图下的固定时间二分一致性问题.首先,本文针对智能体间相互合作与相互竞争的关系,设计了一类存在输入时延的多智能体系统固定时间分布式一致性控制协议,使得系统状态在固定时间内收敛到数值相同但符号相反的两个值,且收敛时间上界与初始状态无关.随后,利用Lyapunov稳定性理论和代数图论给出了在存在输入时延的情况下多智能体系统实现固定时间二分一致性的充分条件和收敛时间的上界值,证明了控制算法的稳定性.最后,仿真实例验证了所提固定时间二分一致性算法和理论结果的有效性.     

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.     

Distributed robust consensus control of multi-agent systems with heterogeneous matching uncertainties

This paper considers the distributed consensus problem of linear multi-agent systems subject to different matching uncertainties for both the cases without and with a leader of bounded unknown control input. Due to the existence of nonidentical uncertainties, the multi-agent systems discussed in this paper are essentially heterogeneous. For the case where the communication graph is undirected and connected, based on the local state information of neighboring agents, a fully distributed continuous adaptive consensus protocol is designed, under which the consensus error is uniformly ultimately bounded and exponentially converges to a small adjustable bounded set. For the case where there exists a leader whose control input is unknown and bounded, a distributed adaptive consensus protocol is proposed to ensure the boundedness of the consensus error. A sufficient condition for the existence of the proposed protocols is that each agent is stabilizable.     

Controllability of heterogeneous multi-agent systems under directed and weighted topology

This paper considers the controllability problem for both continuous- and discrete-time linear heterogeneous multi-agent systems with directed and weighted communication topology. First, two kinds of neighbour-based control protocols based on the distributed protocol of first-order and second-order multi-agent systems are proposed, under which it is shown that a heterogeneous multi-agent system is controllable if the underlying communication topology is controllable. Then, under special leader selection, the result shows that the controllability of a heterogeneous multi-agent system is solely decided by its communication topology graph. Furthermore, some necessary and/or sufficient conditions are derived for controllability of communication topology from algebraic and graphical perspectives. Finally, simulation examples are presented to demonstrate the effectiveness of the theoretical results.     

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.     

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（英文）

This paper considers the cooperative tracking of linear multi-agent systems with a dynamic leader whose input information is unavailable to any followers. Cooperative iterative learning controllers, based on the relative state information of neighboring agents, are proposed for tracking the dynamic leader over directed communication topologies. Stability and convergence of the proposed controllers are established using Lyapunov-Krasovskii functionals. Furthermore, this result is extended to the output feedback case where only the output information of each agent can be obtained. A local observer is constructed to estimate the unmeasurable states. Then, cooperative iterative learning controllers, based on the relative observed states of neighboring agents,are devised. For both cases, it is shown that the multi-agent systems whose communication topologies contain a spanning tree can reach synchronization with the dynamic leader, and meanwhile identify the unknown input of the dynamic leader using distributed iterative learning laws. An illustrative example is provided to verify the proposed control schemes.     

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.     

Cooperative tracking control for linear multi-agent systems with external disturbances under a directed graph

This paper studiesthe cooperative tracking control problem for multi-agent systems with unknown external disturbances under a directed graph. The leader's input is nonzero and unavailable to the followers. Based on the relative output measurements of neighbouring agents, a novel observer-based cooperative tracking protocol is presented, where the a group of intermediate estimators are constructed to estimate the tracking errors and the combined signal of the disturbances and the leader's input simultaneously, then decentralised tracking protocols are designed based on the obtained estimates. The states of the global tracking error system are proved to be uniformly ultimately bounded. A numerical example of aircraft illustrates the effectiveness of the cooperative tracking protocol.     

Consensus in nonlinear multi-agent systems with nonidentical nodes and sampled-data control

This paper primarily discusses the leader-following consensus problem in nonlinear second-order multi-agent systems with nonidentical nodes. Sampled-data-based protocols are applied to reach consensus. Both delay-free and input-delay protocols are proposed. Based on the Lyapunov functional approach and linear matrix inequality (LMI) method, sufficient criteria are obtained to guarantee quasi-consensus for nonlinear heterogeneous multi-agent systems. All the heterogeneous followers can track the leader within a bounded range. Furthermore, the error systems between the leader and each follower eventually converge to a convergence domain that depends on the heterogeneity among the dynamics of the agents. Additionally, leader-following consensus can also be reached as the heterogeneity vanishes. Finally, numerical simulations are provided to illustrate the theoretical results.     

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.     

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

This paper investigates the cooperative global optimal preview tracking problem of linear multi-agent systems under the assumption that the output of a leader is a previewable periodic signal and the topology graph contains a directed spanning tree. First, a type of distributed internal model is introduced, and the cooperative preview tracking problem is converted to a global optimal regulation problem of an augmented system. Second, an optimal controller, which can guarantee the asymptotic stability of the augmented system, is obtained by means of the standard linear quadratic optimal preview control theory. Third, on the basis of proving the existence conditions of the controller, sufficient conditions are given for the original problem to be solvable, meanwhile a cooperative global optimal controller with error integral and preview compensation is derived. Finally, the validity of theoretical results is demonstrated by a numerical simulation.     

Cooperative optimal preview tracking control of continuous-time multi-agent systems

This paper presents the cooperative preview control method for continuous-time multi-agent systems with a time-invariant directed communication topology. First, the cooperative tracking preview control problem is transformed into the optimal regulation problem of an augmented system. Next, by applying the results of the standard optimal preview control of continuous-time linear systems, a controller of the augmented system is obtained. Furthermore, the stabilisability and detectability of the augmented system are studied under the fixed digraph and the prescribed leader. Then, we derive the controller of multi-agent systems with error integral and preview action that can guarantee the achievement of cooperative optimal preview tracking. Finally, the effectiveness of the controller is shown by numerical simulations.     

基于自触发的异构多智能体协同输出调节

本文针对线性异构多智能体系统,基于自适应自触发条件,分别设计了状态和输出反馈协同控制器.其中自适应控制策略可以避免使用多智能体系统的全局信息,从而实现分布式控制;自触发控制不仅可以避免对触发条件进行连续监测,还可以有效地降低网络的通信负载和控制器的更新次数,且不存在芝诺现象.最后通过4个跟随智能体和一个领导智能体进行了协同输出直角编队仿真实验,实现了多智能体系统对外部系统的渐近跟踪和干扰抑制,验证了结果的有效性.     

Event-Triggered Asymmetric Bipartite Consensus Tracking for Nonlinear Multi-Agent Systems Based on Model-Free Adaptive Control

In this paper, an asymmetric bipartite consensus problem for the nonlinear multi-agent systems with cooperative and antagonistic interactions is studied under the event-triggered mechanism. For the agents described by a structurally balanced signed digraph, the asymmetric bipartite consensus objective is firstly defined, assigning the agents’ output to different signs and module values. Considering with the completely unknown dynamics of the agents, a novel event-triggered model-free adaptive bipartite control protocol is designed based on the agents’ triggered outputs and an equivalent compact form data model. By utilizing the Lyapunov analysis method, the threshold of the triggering condition is obtained. Subsequently, the asymptotic convergence of the tracking error is deduced and a sufficient condition is obtained based on the contraction mapping principle. Finally, the simulation example further demonstrates the effectiveness of the protocol.