Fixed-Time Antidisturbance Consensus Tracking for Nonlinear Multiagent Systems With Matching and Mismatching Disturbances

In this paper,fixed-time consensus tracking for mul-tiagent systems(MASs)with dynamics in the form of strict feed-back affine nonlinearity is addressed.A fixed-time antidistur-bance consensus tracking protocol is proposed,which consists of a distributed fixed-time observer,a fixed-time disturbance observer,a nonsmooth antidisturbance backstepping controller,and the fixed-time stability analysis is conducted by using the Lyapunov theory correspondingly.This paper includes three main improvements.First,a distributed fixed-time observer is developed for each follower to obtain an estimate of the leader’s output by utilizing the topology of the communication network.Second,a fixed-time disturbance observer is given to estimate the lumped disturbances for feedforward compensation.Finally,a nonsmooth antidisturbance backstepping tracking controller with feedforward compensation for lumped disturbances is designed.In order to mitigate the“explosion of complexity”in the tradi-tional backstepping approach,we have implemented a modified nonsmooth command filter to enhance the performance of the closed-loop system.The simulation results show that the pro-posed method is effective.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Adaptive Fixed-Time Control of Nonlinear MASs With Actuator Faults

The adaptive fixed-time consensus problem for a class of nonlinear multi-agent systems(MASs)with actuator faults is considered in this paper.To approximate the unknown nonlinear functions in MASs,radial basis function neural networks are used.In addition,the first order sliding mode differentiator is utilized to solve the“explosion of complexity”problem,and a filter error compensation method is proposed to ensure the convergence of filter error in fixed time.With the help of the Nussbaum function,the actuator failure compensation mechanism is constructed.By designing the adaptive fixed-time controller,all signals in MASs are bounded,and the consensus errors between the leader and all followers converge to a small area of origin.Finally,the effectiveness of the proposed control method is verified by simulation examples.

Tracking Control of Multi-Agent Systems Using a Networked Predictive PID Tracking Scheme

With the rapid development of network technology and control technology,a networked multi-agent control system is a key direction of modern industrial control systems,such as industrial Internet systems.This paper studies the tracking control problem of networked multi-agent systems with communication constraints,where each agent has no information on the dynamics of other agents except their outputs.A networked predictive proportional integral derivative(PPID)tracking scheme is proposed to achieve the desired tracking performance,compensate actively for communication delays,and simplify implementation in a distributed manner.This scheme combines the past,present and predictive information of neighbour agents to form a tracking error signal for each agent,and applies the proportional,integral,and derivative of the agent tracking error signal to control each individual agent.The criteria of the stability and output tracking consensus of multi-agent systems with the networked PPID tracking scheme are derived through detailed analysis on the closed-loop systems.The effectiveness of the networked PPID tracking scheme is illustrated via an example.

Adaptive Cyber Defense Technique Based on Multiagent Reinforcement Learning Strategies

The static nature of cyber defense systems gives attackers a sufficient amount of time to explore and further exploit the vulnerabilities of information technology systems.In this paper,we investigate a problem where multiagent sys-tems sensing and acting in an environment contribute to adaptive cyber defense.We present a learning strategy that enables multiple agents to learn optimal poli-cies using multiagent reinforcement learning(MARL).Our proposed approach is inspired by the multiarmed bandits(MAB)learning technique for multiple agents to cooperate in decision making or to work independently.We study a MAB approach in which defenders visit a system multiple times in an alternating fash-ion to maximize their rewards and protect their system.We find that this game can be modeled from an individual player’s perspective as a restless MAB problem.We discover further results when the MAB takes the form of a pure birth process,such as a myopic optimal policy,as well as providing environments that offer the necessary incentives required for cooperation in multiplayer projects.

基于MultiAgent和CSCW的多媒体教学模型

生于MultiAgent和CSCW的观点，提出一个多媒体教学模型．探讨了该模型的结构以及模型中Agent的表示、通信等关键技术。

基于Multiagent生态进化算法实现个性化主动信息服务

网络资源的指数膨胀，使得用户在获得自己需要的信息资源时要花费大量的时间和精力。该文采用Multiagent技术协助用户获取需要的信息资源，以节省用户的时间。同时给出了一种生态进化算法，使得Agent可以逐渐把握用户的需求、适应用户需求的变化、探索用户可能感兴趣的领域，为用户提供个性化的主动信息服务。

基于多智能体的梯级水电联合运行决策支持系统

以复杂系统自组织理论与multiagent分布式建模技术为基础,通过对流域梯级水电联合运行与调度过程的自组织行为特征的分析,建立基于multiagent理论的决策模型,实时采集流域的水情、雨情、工情、电情(如各电站机组出力、负荷分配、运行方式、全厂功率总和等),模拟仿真流域梯级水电联合运行与调度的决策过程,合理进行流域梯级水能的综合利用和发电生产以及跨流域补偿联合运行与调度,实现流域梯级水电联合运行与调度重大决策的动态预演,为梯级水电联合运行提供经济、高效、实时的决策支持。

多主体撮合交易系统的设计与实现

研究了电子商务交易模型的实现机制,设计了基于 Multi-Agent 的电子商务交易市场的组织结构,在基于Multi-Agent 的撮合交易系统中,把整个交易过程看成一个动态的交互过程,体现了 Multi—Agent 系统的动态特性,同时引入强化学习算法对竞标策略进行动态修正,使多主体撮合交易系统具有一定的自均衡和自学习能力。试验表明,基于多主体的撮合交易模型和动态竞标机制具有较好的交易性能。

基于Multi Agent的图象理解

最近十多年来 ,具有专家系统外壳的图象理解软件的开发一直是一个重要的研究课题。然而 ,多数基于知识的图象理解系统或者局限于诸如分割之类的特定图象操作上 ,或者局限于像理解建筑物的航空图象这样特定的应用。由于这些系统的目标和知识结构的局限性 ,因而不能将它们推广到其它领域。此研究就是试图解决此问题 :首先将Agent构造环境扩展为一个MultiAgent的图象理解系统 ,而此系统是知识入口的开发工具 ,它为用户提供一个类似于专家系统外壳的界面。这样一方面能加速图象理解系统的开发 ,另一方面方便那些缺乏图象理解知识的人开发图象理解应用程序。

Multiagent系统通讯及单元可靠性综合评测

为了更准确的评测Multiagent系统可靠性,提出了将通讯可靠性、单元可靠性及系统拓扑结构都考虑在评测过程中的综合评测方法.该方法概括出Multiagent系统的结构,釆用基于马尔可夫过程的方法,分析通讯可靠性、单元可靠性等因素对集中式、分布式及联邦式Multiagent系统可靠性的影响,并给出了系统可靠性评测模型.仿真结果表明,该方法能够将复杂系统的可靠性评测问题分解为简单的形式.针对各分解后的结构进行评测,进一步得到了整个系统的可靠性.

网络信息发现系统中Multiagent的研究与设计

随着因特网的快速发展 ,分布式应用开发越来越受到人们的重视。而现有的几种分布计算技术的不足已逐渐显露。本文介绍了 Multiagent技术及其发展 ,提出了一种以 Multiagent技术为基础 ,通过多个分布 Agent之间的协作共同完成网络信息发现的系统设计思想。

定题检索MultiAgent的研究与设计

本文详细介绍了定题检索Agent的系统结构和技术特点。通过对Agent的信息搜索原理以及关键技术的剖析,提出了一种以Multiagent技术为基础,多个分布Agent之间的协同工作,共同完成网络信息发现的系统设计思想。

应用MultiAgent优化自主导航系统

本文针对自主导航系统的多任务执行时容易产生的冲突问题,将系统进行功能分解,采用MultiAgent技术,由各个智能体共同执行完成系统功能。着重介绍了系统中各个代理的个体规划和社会规划,对各个Agent的可能产生的行为冲突和资源冲突进行了分析并提出相应避让策略。系统的实现采用了多线程技术,各个Agent之间的通信采用KQML的简化集。改进后的系统性能良好,无冲突现象。

开发“网络课程”的几种信息技术

本文阐述了“网络课程”的概念,介绍了与开发优质网络课程相关的四种重要信息技术:Mu ltiA-gents技术,XML技术,GR ID技术和NLP技术。

基于Multiagent的社交网络舆情传播模型

为分析与预测社交网络中舆情传播过程和演化趋势,本文基于Multiagent分布式技术,建立了社交网络舆情传播模型,研究社交网络舆情传播方式,并根据Agent的行为和状态特性,对Agent进行分类,分析Agent的属性特征,通过剖析Agent个体之间的交互微观行为,依据信息价值时效性、信息源覆盖率和信息关注度,对转发行为的影响进行讨论,给出了Agent的决策规则,以网络结构方式体现Agent之间的内在联系。为验证模型的有效性,基于Agent的仿真平台,采用Netlogo 6.0.4进行模拟仿真分析。仿真结果表明,舆情信息的传播与信息价值呈正相关,信息价值越大,越有利于舆情信息的传播,且信息源的覆盖率与转发Agent数和中止Agent数成正相关,信息关注度对舆情传播影响甚大,说明该模型能准确分析和预测网络中舆情传播的演化趋势。该研究对相关人员了解社交网络中舆情的传播具有重要意义。

Physical Safety and Cyber Security Analysis of Multi-Agent Systems:A Survey of Recent Advances

Multi-agent systems(MASs)are typically composed of multiple smart entities with independent sensing,communication,computing,and decision-making capabilities.Nowadays,MASs have a wide range of applications in smart grids,smart manufacturing,sensor networks,and intelligent transportation systems.Control of the MASs are often coordinated through information interaction among agents,which is one of the most important factors affecting coordination and cooperation performance.However,unexpected physical faults and cyber attacks on a single agent may spread to other agents via information interaction very quickly,and thus could lead to severe degradation of the whole system performance and even destruction of MASs.This paper is concerned with the safety/security analysis and synthesis of MASs arising from physical faults and cyber attacks,and our goal is to present a comprehensive survey on recent results on fault estimation,detection,diagnosis and fault-tolerant control of MASs,and cyber attack detection and secure control of MASs subject to two typical cyber attacks.Finally,the paper concludes with some potential future research topics on the security issues of MASs.

Containment Control of Fractional Order Multi-Agent Systems With Time Delays

In complex environments, many distributed multiagent systems are described with the fractional-order dynamics.In this paper, containment control of fractional-order multiagent systems with multiple leader agents are studied. Firstly,the collaborative control of fractional-order multi-agent systems(FOMAS) with multiple leaders is analyzed in a directed network without delays. Then, by using Laplace transform and frequency domain theorem, containment consensus of networked FOMAS with time delays is investigated in an undirected network, and a critical value of delays is obtained to ensure the containment consensus of FOMAS. Finally, numerical simulations are shown to verify the results.

Self-organized motion in anisotropic swarms

This paper considers an anisotropic swarm model with a class of attraction and repulsion functions. It is shown that the members of the swarm will aggregate and eventually form a cohesive cluster of finite size around the swarm center. Moreover, It is also proved that under certain conditions, the swarm system can be completely stable, i.e., every solution converges to the equilibrium points of the system. The model and results of this paper extend a recent work on isotropic swarms to more general cases and provide further insight into the effect of the interaction pattern on self-organized motion in a swarm system. Keywords Biological systems - Multiagent systems - Pattern formation - Stability - Swarms This work was supported by the National Natural Science Foundation of China (No. 60274001 and No. 10372002) and the National Key Basic Research and Development Program (No.2002CB312200).

Limited-Budget Consensus Design and Analysis for Multiagent Systems With Switching Topologies and Intermittent Communications

This paper investigates limited-budget consensus design and analysis problems of general high-order multiagent systems with intermittent communications and switching topologies.The main contribution of this paper is that the tradeoff design between the energy consumption and the consensus performance can be realized while achieving leaderless or leaderfollowing consensus,under constraints of limited budgets and intermittent communications.Firstly,a new intermittent limitedbudget consensus control protocol with a practical trade-off design index is proposed,where the total budget of the whole multiagent system is limited.Then,leaderless limited-budget consensus design and analysis criteria are derived,in which the matrix variables of linear matrix inequalities are determined according to the total budget and the practical trade-off design parameters.Meanwhile,an explicit formulation of the consensus function is derived to describe the consensus state trajectory of the whole system.Moreover,a new two-stage transformation strategy is utilized for leader-following cases,by which the dynamics decomposition of leaderless and leader-following cases can be converted into a unified framework,and sufficient conditions of the leader-following limited-budget consensus design and analysis are determined via those of the leaderless cases.Finally,numerical simulations are given to illustrate theoretical results.