Robust Consensus and Soft Control of Multi-Agent Systems with Noises*

This paper considers the problem of robust consensus for a basic class of multi-agent systems with bounded disturbances and with directed information flow. A necessary and sufficient condition on the robust consensus is first presented, which is then applied to the analysis, control and decision making problems in the noise environments. In particular, the authors show how a soft control technique will synchronize a group of autonomous mobile agents without changing the existing local rule of interactions, and without assuming any kind of connectivity conditions on the system trajectories.     

用层次颜色Petri网模拟主体行为

智能主体动态动作的形式化描述是开发应用多主体系统的的形式化描述多是基于逻辑学的描述,不易直接应用到系统开发中.该文通过利用层次颜色Petri网对市场多主体系统的模拟,提出并讨论了利用层次颜色Petri网为多主体系统建模、模拟主体行为的方法,该方法对多主体系统中主体间的各种动态关系有较好的刻画,并且通过层次化的方法减少了利用一般Petri网系统(如P/T系统)模拟复杂系统时所遇到的难度.     

单边Lipschitz非线性多智能体系统一致性追踪控制

针对单边Lipschitz非线性多智能体系统,提出了一种分布式一致性控制方法.首先,构建了领导-跟随者动力学结构,用于实现单边Lipschitz多智能体系统的追踪控制.然后,设计了单边Lipschitz非线性多智能体系统的一致性控制协议,可根据智能体之间局部交互信息构建分布式反馈控制,并将系统的一致性追踪问题转化为系统...     

COOPERATIVE DYNAMICS OF LOYAL CUSTOMERS IN QUEUEING NETWORKS

We consider queueing networks （QN＇s） with feedback loops roamed by ＂intelligent＂ agents, able to select their routing on the basis of their measured waiting times at the QN nodes. This is an idealized model to discuss the dynamics of customers who stay loyal to a service supplier, provided their service time remains below a critical threshold. For these QN＇s, we show that the traffic flows may exhibit collective patterns typically encountered in multi-agent systems. In simple network topologies, the emergent cooperative behaviors manifest themselves via stable macroscopic temporal oscillations, synchronization of the queue contents and stabilization by noise phenomena. For a wide range of control parameters, the underlying presence of the law of large numbers enables us to use deterministic evolution laws to analytically characterize the cooperative evolution of our multi-agent systems. In particular, we study the case where the servers are sporadically subject, to failures altering their ordinary behavior.     

Formation Tracking for Nonlinear Multi-agent Systems with Input and Output Quantization via Adaptive Output Feedback Control

Signal quantization can reduce communication burden in multi-agent systems, whereas it brings control challenge to multi-agent formation tracking. This paper studies the output feedback control problem for formation tracking of multi-agent systems with both quantized input and output.The agents are described by a nonlinear dynamic model with unknown parameters and immeasurable states. To estimate immeasurable states and solve the uncertainties, state observers are developed by using dynamic high-gain tools. Through proper parameter designs, an output feedback quantized controller is established based on quantized output signals, and the quantization effect on the control system is eliminated. Stability analysis proves that, with the proposed control scheme, multi-agent systems can track the reference trajectory while forming and maintaining the desired formation shape.In addition, all the signals in the closed-loop systems are bounded. Finally, the numerical simulation and practical experiment are provided to verify the theoretical analysis.     

Uncoupled PID Control of Coupled Multi-Agent Nonlinear Uncertain systems

In this paper, PID (proportional-integral-derivative) controllers will be designed to solve the tracking problem for a class of coupled multi-agent systems, where each agent is described by a second-order high-dimensional nonlinear uncertain dynamical system, which only has access to its own tracking error information and does not need to communicate with others. This paper will show that a 3-dimensional manifold can be constructed based on the information about the Lipschitz constants of the system nonlinear dynamics, such that whenever the three parameters of each PID controller are chosen from the manifold, the whole multi-agent system can be stabilized globally and the tracking error of each agent approaches to zero asymptotically. For a class of coupled first-order multi-agent nonlinear uncertain systems, a PI controller will be designed to stabilize the whole system.     

Output consensus for heterogeneous nonlinear multi-agent systems based on T-S fuzzy model

In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the nonlinear agents’ dynamics. Based on the model, a distributed fuzzy observer and controller are designed based on parallel distributed compensation scheme and internal reference models such that the heterogeneous nonlinear multi-agent systems can achieve output consensus. Then a necessary and sufficient condition is presented for the output consensus problem. And it is shown that the consensus trajectory of the global fuzzy model is determined by the network topology and the initial states of the internal reference models. Finally, some simulations are given to illustrate and verify the effectiveness of the proposed scheme.     

Cluster-Delay Consensus for Second-Order Nonlinear Multi-agent Systems

This paper investigates the second-order nonlinear multi-agent systems subject to the cluster-delay consensus. The multi-agent systems consist of leader and agents, whose dynamics are second-order nonlinear. The objective is that the agents track the leader asymptotically with different time delays, i.e., the agents in different groups reach delay consensus, while the agents in the same group reach identical consensus. To guarantee the cluster-delay consensus for the second-order multi-agent systems, a new control protocol is proposed. Then some corresponding conditions for cluster-delay consensus are derived by using Lyapunov directed method and matrix theory. Finally, the effectiveness of the theoretical analysis results are verified by some numerical simulations.     

装备虚拟维修训练系统设计方法研究

开发虚拟维修训练系统是一项复杂的系统工程,Agent的理论、技术为大型、复杂系统的分析、设计和实现提供了一个崭新的途径,介绍了多Agent系统工程(MaSE)方法及其开发工具agentTool,针对传统软件开发方法的局限性,运用MaSE方法指导虚拟维修训练系统的分析、设计和开发,提出了一种基于Multi-Agent的虚拟维修训练系统(VMTS)结构框架,整个系统分别由7个具有交互作用的Agent组成,并运用图形模型描述了系统目标、行为、角色、Agent类型及Agent之间的通信接口,从而将VMTS转化为一个多Agent系统的设计与开发,提高了系统的健壮性、灵活性和可重用性。     

采用平均加权的ad hoc网络分布式时隙同步算法

为了降低现有ad hoc网络分布式时隙同步算法复杂度,基于研究多个体系统行为特征的Vicsek模型,提出一种采用平均加权的分布式时隙同步算法。各节点通过计算自身及其邻节点时隙起始时刻的算术平均调整时隙位置,最终达到所有节点时隙位置的统一,实现全网同步。对算法在不同网络连接下的收敛性进行逐一分析,并对网络节点随机分布时的算法收敛性进行仿真,结果表明,算法适用于各种连通性网络且收敛速度较快。     

SOFT CONTROL ON COLLECTIVE BEHAVIOR OF A GROUP OF AUTONOMOUS AGENTS BY A SHILL AGENT

This paper asks a new question： how can we control the collective behavior of self-organized multi-agent systems？ We try to answer the question by proposing a new notion called ＇Soft Control＇ which keeps the local rule of the existing agents in the system. We show the feasibility of soft control by a case study. Consider the simple but typical distributed multi-agent model proposed by Vicsek et al. for flocking of birds： each agent moves with the same speed but with different headings which are updated using a local rule based on the average of its own heading and the headings of its neighbors. Most studies of this model are about the self-organized collective behavior, such as synchronization of headings. We want to intervene in the collective behavior （headings） of the group by soft control. A specified method is to add a special agent, called a ＇Shill＇, which can be controlled by us but is treated as an ordinary agent by other agents. We construct a control law for the shill so that it can synchronize the whole group to an objective heading. This control law is proved to be effective analytically and numerieally. Note that soft control is different from the approach of distributed control. It is a natural way to intervene in the distributed systems. It may bring out many interesting issues and challenges on the control of complex systems.     

Cooperative Neuro Adaptive Control of Leader Following Uncertain Multi-Agent Systems with Unknown Hysteresis and Dead-Zone

In this paper, a cooperative adaptive control of leader-following uncertain nonlinear multiagent systems is proposed. The communication network is weighted undirected graph with fixed topology. The uncertain nonlinear model for each agent is a higher-order integrator with unknown nonlinear functions, unknown disturbances and unknown input actuators. Meanwhile, the gains of input actuators are unknown nonlinear functions with unknown sign. Two most common behaviors of input actuators in practical applications are hysteresis and dead-zone. In this paper, backlash-like hysteresis and dead-zone are used to model the input actuators. Using universal approximation theorem proved for neural networks, the unknown nonlinear functions are tackled. The unknown weights of neural networks are derived by proposing appropriate adaptive laws. To cope with modeling errors and disturbances an adaptive robust structure is proposed. Considering Lyapunov synthesis approach not only all the adaptive laws are derived but also it is proved that the closed-loop network is cooperatively semi-globally uniformly ultimately bounded(CSUUB). In order to investigate the effectiveness of the proposed method, it is applied to agents modeled with highly nonlinear mathematical equations and inverted pendulums. Simulation results demonstrate the effectiveness and applicability of the proposed method in dealing with both numerical and practical multi-agent systems.     

信息物理融合系统可信软件形式化建模与分析

从多Agent系统的角度,以Petri网和π演算为语义基础,建立了一种信息物理融合系统（cyber-physical systems,CPS）可信软件形式化模型（high-confidence software formal model,HCSFM）. HCSFM以Petri网形象地描述CPS可信软件静态结构模型及动态行为,用Petri网分析方法和支持工具对模型进行分析和验证; 利用π演算刻画CPS可信软件中Agent的加入、退出、更新和体系结构重配置等动态演化机制,并研究Agent的演化策略及演化后CPS的一致性,确保动态演化后CPS软件能正常交互,从而为CPS软件设计提供可信保障. 通过HCSFM在无人驾驶车辆编队CPS中的应用,表明HCSFM可以有效地对CPS可信软件进行建模和分析.     

RELAXED CONDITIONS FOR CONSENSUS IN MULTI-AGENT COORDINATION

This paper proposes relaxed sufficient conditions for the consensus of multi-agent systems by the averaging protocols with time-varying system topology. Bidirectional information exchange between neighboring agents is considered and both the discrete-time and continuous-time consensus protocols are studied. It is shown that the consensus is reached if there exists an unbounded time sequence such that two agents who own the maximum and minimum states at each time instant in the sequence will be jointly connected at some future time. Further, this result is applied to the original nonlinear Vicsek model, and a sufficient condition for the heading consensus of the group with restricted initial conditions is obtained.     

面向Agent方法在计算机生成兵力中的应用研究

计算机生成兵力（CGF）具有主自性，智能性等特征，并具备感知，通信以及协调的艰力，面向Agent的分析开发方法可以借鉴到CGF系统研究开发工作，CGF所研究的内容侧重于Agent结构，感知，认知，决策等行为的描述，以及多Agent系统（MAS）的研究，本文首先对Agent的一航概念做了介绍，总结了计算机生成兵力中Agent应具有的性质，讨论了设计和建造CGF中Agent的一些问题以及多Agent之间的协作问题，文中最后给出了CGF中Agent设计的概念模型。     

基于扩展UML的多Agent系统建模方法

基于对象和Agent概念的一致性 ,在多Agent系统的建模过程中 ,利用已经比较成熟的面向对象技术是一种值得重视的方法。在分析了统一建模语言 (UML)的基本建模思想和基于组织分析的多Agent系统建模思路基础上 ,以一个分布式后勤管理系统的分析为例 ,从Agent组织的角色定义、静态组织结构描述和动态行为描述等三方面给出了基于扩展UML的多Agent系统建模的主要步骤和方法     

Event-Triggered Sampled-Data Consensus of Nonlinear Multi-Agent Systems with Control Input Losses

This paper investigates the leader-following consensus problem for multi-agent systems with event-triggered mechanism and control packet losses. Based on the local synchronization error, event-triggered mechanisms are proposed in order to reduce the number of controller update. The control packet may lose due to unreliability of communication channel. With the assumption that once the packet loss happens the controller will be set to zero, sufficient consensus criteria for multi-agent system with event-triggered mechanism and control packet losses is obtained. It is also shown that the interplay among the allowable packet loss rate, event-triggered mechanism and sampling period. An illustrative example is given to demonstrate the effectiveness of the theoretical results.     

A message-driving formalism for modeling and simulation of multi-agent supply chain systems

To acquire a competitive advantage in the expanding market, manufacturing enterprises should be able to manage their supply chains as effectively as possible. It is now becoming popular to model supply chains as multi-agent systems and use discrete event simulation to learn more about their behaviors or investigate the implications of alternative configurations. In order to enhance the computational efficiency and keep the simulation credibility, this paper proposes a message-driving formalism for the simulation of multi-agent supply chain systems. Through the message-driving formalism, the problem of shared variables is addressed and the parallel operation of agents is implemented. Simulation experiments with a prototype implementation show that the message-driving formalism is able to provide credible results in significantly less simulation time.     

具有混合执行器故障的多智能体分布式有限时间自适应协同容错控制

针对多智能体编队系统执行器发生故障时,所引起的参数不确定以及系统瞬态不稳定问题,本文采用径向基函数神经网络(radial basis function neural networks,RBFNNs)对不确定参数(未知函数)进行估计.同时,基于反推技术设计出合理的自适应容错控制器,并通过有限时间理论保证系统实现瞬态稳定....     

基于Multi-Agent的面向过程混杂系统的集成技术

基于 Multi-Agent提出了面向过程的混杂系统的集成框架 ,设计了用于该框架的单个 Agent的基本模型 ,分析了异构 Agent之间的关系 ,给出了一种新颖的 Agent变迁策略 .该框架能有效地刻画复杂过程控制系统的动态行为 ,便于系统的分析和设计 .