Iterative learning approaches to design finite-time consensus protocols for multi-agent systems

In this paper, the finite-time output consensus problem of multi-agent systems is considered by using the iterative learning control (ILC) approach. Two classes of distributed protocols are constructed from the two-dimensional system point of view (with time step and iteration number as independent variables), and are termed as iterative learning protocols. If learning gains are chosen appropriately, then all agents in a directed graph can be enabled to achieve finite-time consensus with the iterative learning protocols. Moreover, all agents in a directed graph can be guaranteed to reach finite-time consensus at any desired terminal output if the iterative learning protocols are improved by introducing the desired terminal output to some (not necessarily all) of the agents. Simulation results are finally presented to illustrate the performance and effectiveness of our iterative learning protocols.     

Robust iterative learning protocols for finite-time consensus of multi-agent systems with interval uncertain topologies

This paper is devoted to the robust finite-time output consensus problems of multi-agent systems under directed graphs, where all agents and their communication topologies are subject to interval uncertainties. Distributed protocols are constructed by using iterative learning control (ILC) algorithms, where information is exchanged only at the end of one iteration and learning is used to update the control inputs after each iteration. It is proved that under ILC-based protocols, the finite-time consensus can be achieved with an increasing number of iterations if the communication network of agents is guaranteed to have a spanning tree. Moreover, if the information of any desired terminal output is available to a portion (not necessarily all) of the agents, then the consensus output that all agents finally reach can be enabled to be the desired terminal output. It is also proved that for all ILC-based protocols, gain selections can be provided in terms of bound values, and consensus conditions can be developed associated with bound matrices. Simulation results are given to demonstrate the effectiveness of our theoretical results.     

基于迭代学习的多智能体系统分布式跟踪控制

文章考虑了具适多智能体系统的分布式跟踪控制问题。通过设计带有初始学习机制的$P$型和$PD^{\alpha}$ 型迭代学习控制策略求解跟踪问题。具适导数具有良好的性质且可以刻画不同步长的实际数据采样情况。初始学习机制放松了初始值条件且提高了算法实现趋同跟踪的性能。在可重复操作环境和有向通信拓扑的假设下,提出了一种分布式迭代学习方案,通过重复同一轨迹的控制尝试和用跟踪误差修正不满意的控制信号来实现有限时间趋同。严格证明了随着迭代次数增加,提出的$P$型和$PD^{\alpha}$ 型迭代学习控制策略使得所有智能体能渐近跟踪上参考轨迹。两个代表性数值仿真验证了算法的有效性。     

输出饱和多智能体系统的迭代学习趋同跟踪控制

针对带有输出饱和的多智能体系统有限时间趋同跟踪控制问题,提出了一种分布式迭代学习控制算法.首先假设多智能体系统具有固定拓扑结构,且仅有部分智能体可获取到期望轨迹信息.基于输出约束条件构造一致性跟踪误差,在此基础上设计了P型迭代学习控制率.然后采用压缩映射方法给出了一个算法收敛的充分条件,并在理论上证明了跟踪误差的收敛性.最后,将理论结果推广至具有随机切换拓扑结构的多智能体系统中.仿真结果验证了所提出算法的有效性.     

Finite-time consensus for multi-agent systems via nonlinear control protocols

This paper investigates the fnite-time consensus problem of multi-agent systems with single and double integrator dynamics,respectively.Some novel nonlinear protocols are constructed for frst-order and second-order leader-follower multi-agent systems,respectively.Based on the fnite-time control technique,the graph theory and Lyapunov direct method,some theoretical results are proposed to ensure that the states of all the follower agents can converge to its leader agent s state in fnite time.Finally,some simulation results are presented to illustrate the efectiveness of our theoretical results.     

Consensus seeking of multi-agent systems from an iterative learning perspective

The consensus seeking problems for both discrete and continuous multi-agent networks are discussed from an iterative learning perspective. It is shown that the consensus seeking process can be viewed as an iterative learning process for agents under directed networks to improve their performances from time to time in order to achieve consensus. If a desired consensus state is specified, then the multi-agent system can be guaranteed to reach consensus through reducing the tracking error between each agent’s state and the desired consensus state monotonically to zero with respect to the increasing of time. If there is no desired consensus state, then the agents can achieve consensus through reducing their states monotonically to the minimum quantity with increasing time. Simulations illustrate the observed results.     

DoS攻击下多智能体系统无模型自适应迭代学习跟踪控制EI北大核心CSCD

针对周期性拒绝服务(DoS)攻击下多智能体系统有限时间趋同跟踪控制问题,本文提出了一种无模型自适应迭代学习控制(MFAILC)算法.假设多智能体系统具有固定拓扑结构,并且仅有部分智能体可获取到期望轨迹信息.在多智能体系统数据传输过程中,需要经由对数量化器进行量化处理.首先,使用伪偏导数将智能体系统动态线性化,处理过程中考虑符合伯努利分布的周期性DoS攻击现象,在此基础上设计了MFAILC控制算法,其次,采用压缩映射方法给出了一个在期望意义下保证跟踪误差收敛的充分条件,并在理论上证明了所提算法的收敛性.所提算法只需利用系统的输入输出数据就可完成趋同跟踪任务.最后,仿真结果验证了所提算法的有效性.     

Robust finite-time consensus tracking for second-order multi-agent systems with input saturation under general directed communication graphs

In this paper, we study the global finite-time consensus tracking problem for uncertain second-order multi-agent systems subject to input saturation. The communication graphs are allowed to be general directed graphs. Sliding-mode observer-based distributed controllers are proposed such that global finite-time consensus tracking is achieved with bounded control inputs. Only relative state or output measurements are used in the proposed controller which reduces the communication requirement on the agents. Simulation examples are given to illustrate the effectiveness of the proposed control strategies.     

初始误差修正的多智能体一致性迭代学习控制

研究了重复运行的分布式多智能体系统在有限时间内的一致性问题。针对具有固定拓扑结构的多智能体系统,在期望轨迹对应的初始状态未知,且系统存在干扰的情况下,引入虚拟领导者技术,提出了一种同时对各智能体的输入和初始状态误差进行迭代修正的分布式学习控制算法。收敛性分析表明,该算法能够消除由于各智能体初始状态和期望轨迹对应的初始状态不同而引起的各智能体输出不能完全跟踪期望轨迹的状况,实现系统在有限时间内的完全跟踪;仿真结果也证明了算法的有效性。     

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（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.     

Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics

In this paper, we discuss the finite-time consensus problem for leaderless and leader–follower multi-agent systems with external disturbances. Based on the finite-time control technique, continuous distributed control algorithms are designed for these agents described by double integrators. Firstly, for the leaderless multi-agent systems, it is shown that the states of all agents can reach a consensus in finite time in the absence of disturbances. In the presence of disturbances, the steady-state errors of any two agents can reach a region in finite time. Secondly, for the leader–follower multi-agent systems, finite-time consensus algorithms are also designed based on distributed finite-time observers. Rigorous proof is given by using Lyapunov theory and graph theory. Finally, one example is employed to verify the efficiency of the proposed method.     

Finite-time formation control for multi-agent systems

In this paper, we develop a new finite-time formation control framework for multi-agent systems with a large population of members. In this framework, we divide the formation information into two independent parts, namely, the global information and the local information. The global formation information decides the geometric pattern of the desired formation. Furthermore, it is assumed that only a small number of agents, which are responsible for the navigation of the whole team, can obtain the global formation information, and the other agents regulate their positions by the local information in a distributed manner. This approach can greatly reduce the data exchange and can easily realize various kinds of complex formations. As a theoretical preparation, we first propose a class of nonlinear consensus protocols, which ensures that the related states of all agents will reach an agreement in a finite time under suitable conditions. And then we apply these consensus protocols to the formation control, including time-invariant formation, time-varying formation and trajectory tracking, respectively. It is shown that all agents will maintain the expected formation in a finite time. Finally, several simulations are worked out to illustrate the effectiveness of our theoretical results.     

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。     

基于事件触发非线性多智能体系统的固定时间一致性

本文研究了在有向拓扑下,带有非线性动力学多智能体系统的固定时间一致性问题.提出了一种新的基于事件触发机制的非线性控制策略,对于每个智能体给出了基于状态信息的事件触发条件,当状态误差满足所给条件时才触发事件,能有效的减小系统的能量耗散和控制器的更新频次.利用Lyapunov稳定性理论和代数图论,证明在该控制策略下,多智能体系统在固定时间能实现领导跟随一致性,且不存在Zeno行为.相较于有限时间一致性策略,采用固定时间一致性策略系统的收敛时间不再依赖于系统的初始状态.最后,仿真实例验证了理论结果的有效性.     

异构多智能体系统有限时间一致性分析

研究二阶智能体速度不可测情况下由一阶和二阶智能体构成的异构多智能体系统有限时间一致性问题。在固定拓扑结构下,给出了异构系统实现一致性的控制协议,通过LaSalle不变集原理和齐次控制方法得到了异构系统有限时间一致性的充分条件;在切换拓扑结构下,给出了异构系统一致性的控制协议,得到了异构系统有限时间一致性的充分条件。仿真结果验证了相关结果的有效性。     

线性和非线性动态异构多自主体系统的有限时间一致性（英文）

In this paper, the finite-time consensus problems of heterogeneous multi-agent systems composed of both linear and nonlinear dynamics agents are investigated. Nonlinear consensus protocols are proposed for the heterogeneous multi-agent systems.Some sufficient conditions for the finite-time consensus are established in the leaderless and leader-following cases. The results are also extended to the case where the communication topology is directed and satisfies a detailed balance condition on coupling weights.At last, some simulation results are given to illustrate the effectiveness of the obtained theoretical results.     

线性和非线性动态异构多自主体系统的有限时间一致性

研究了由线性和非线性动态自主体组成的异构多自主体系统的有限时间一致性问题.针对该异构系统提出了非线性的一致性协议,并分别给出了无领航者和有领航者情形下异构系统在有限时间内实现一致性的充分条件.所得结果还推广到具有有向通信拓扑且满足细致平衡条件的多自主体系统情形.最后,给出一些仿真结果来验证所得结论的正确性和有效性.     

Adaptive iterative learning control for coordination of second‐order multi‐agent systems

In this paper, an efficient framework is proposed to the consensus and formation control of distributed multi‐agent systems with second‐order dynamics and unknown time‐varying parameters, by means of an adaptive iterative learning control approach. Under the assumption that the acceleration of the leader is unknown to any follower agents, a new adaptive auxiliary control and the distributed adaptive iterative learning protocols are designed. Then, all follower agents track the leader uniformly on [0,T] for consensus problem and keep the desired distance from the leader and achieve velocity consensus uniformly on [0,T] for the formation problem, respectively. The distributed multi‐agent coordinations performance is analyzed based on the Lyapunov stability theory. Finally, simulation examples are given to illustrate the effectiveness of the proposed protocols in this paper.Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed Self-triggered Control for Consensus of Multi-agent Systems

This paper studies the consensus problem of general linear multi-agent systems via self-triggered control. Two distributed self-triggered control schemes based on state feedback and output feedback are developed respectively. It is shown that under the proposed control protocols, consensus can be reached if the communication graph of the multi-agent system is connected. An example is presented to illustrate the effectiveness of the proposed control methods.