多智能体网络一致性鲁棒H_∞控制问题

研究了具有不确定性的、定拓扑、无向图多智能体网络的一致性问题,采用鲁棒H∞控制的方法,得到了使各智能体渐近一致并满足干扰衰减性能指标的条件。最后,通过数值仿真验证了所得结论的有效性。     

Distributed Algorithm for Robust Resource Allocation with Polyhedral Uncertain Allocation Parameters

This paper studies a distributed robust resource allocation problem with nonsmooth objective functions under polyhedral uncertain allocation parameters. In the considered distributed robust resource allocation problem, the (nonsmooth) objective function is a sum of local convex objective functions assigned to agents in a multi-agent network. Each agent has a private feasible set and decides a local variable, and all the local variables are coupled with a global affine inequality constraint, which is subject to polyhedral uncertain parameters. With the duality theory of convex optimization, the authors derive a robust counterpart of the robust resource allocation problem. Based on the robust counterpart, the authors propose a novel distributed continuous-time algorithm, in which each agent only knows its local objective function, local uncertainty parameter, local constraint set, and its neighbors’ information. Using the stability theory of differential inclusions, the authors show that the algorithm is able to find the optimal solution under some mild conditions. Finally, the authors give an example to illustrate the efficacy of the proposed algorithm.     

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.     

Consensus for Heterogeneous Multi-Agent Systems with Directed Network Topologies

In this paper, the consensus problem for heterogeneous multi-agent systems composed of first-order and second-order agents is investigated with directed network topologies. Based on a system transformation method, this consensus problem is turned into a consensus problem for homogeneous multi-agent systems. With certain assumption on the control parameters, firstly, necessary and sufficient condition for consensus is proposed with fixed topology. Secondly, sufficient condition is proposed for heterogeneous multi-agent systems to achieve consensus with switching topologies. Finally, simulation examples are presented to verify the effectiveness of the theoretical results.     

Sliding Mode Formation Control of Nonlinear Multi-agent Systems with Local Lipschitz Continuous Dynamics

In this paper, the multi-agent formation problem of networked nonlinear multi-agent systems with local Lipschitz continuous dynamics under directed interaction topology, is investigated.Based on the nonlinear dynamics satisfying locally Lipschitz continuous conditions, three kinds of sliding mode controllers are proposed to solve the problem of multi-agent formation control. Using integral sliding mode controller in first-order system, formation shape is achieved within finite time.For second-order system, on the one hand, non-singular terminal sliding mode function is adopted to accomplish the system asymptotic convergence. Furthermore, super-twisting algorithm is proposed to make multi-agent achieve the desired formation within finite time. Lyapunov functions are applied in the whole paper to ensure the system stability. Numerical simulation examples are provided to demonstrate the effectiveness of the proposed sliding mode control methods.     

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...     

DIDSS环境下信息agent系统任务规范的分解

提出一个基于GDF(扩展决策函数)的多agent任务规范分解判据，提出多agent的任务规范分解性质；将多agent任务规范分解问题等价为建立一个与信息agent任务规范属性相关的MSBN(多模块贝叶斯网)问题，并证明了MSBN的d-cutset(d-割集)和分解判据之间的关系，提出了与多agent任务规范对应的MSBN的分解方法．最后通过示例验证了所提出的方法的可行性。     

具有不同输入时延的二阶多智能体系统一致性

研究了具有不同时变输入时延的二阶连续多智能体系统的一致性问题。首先,通过变量转换,将系统的收敛性问题转化为误差系统的稳定问题;然后,通过对系统进行变换,将二阶系统稳定性问题转换为等价系统的稳定性问题。通过构造李雅普诺夫函数,基于线性矩阵不等式(LMI)的方法,给出在无向固定拓扑条件下,系统达到一致的充分条件。最后,仿真实例证明了结果的有效性。     

Time-Variant Consensus Tracking Control for Networked Planar Multi-Agent Systems with Non-Holonomic Constraints

A time-variant consensus tracking control problem for networked planar multi-agent systems with non-holonomic constraints is investigated in this paper. In the time-variant consensus tracking problem, a leader agent is expected to track a desired reference input, simultaneously, follower agents are expected to maintain a time-variant formation. To solve the time-variant consensus tracking problem of planar multi-agent systems with non-holonomic constraints, a time-variant consensus tracking control strategy is designed on the basis of an unidirectional topology structure. One of main contributions of this paper is the time-variant consensus tracking protocol for general time-variant formations of planar multi-agent systems with non-holonomic constraints, the other main contribution of this paper is an active predictive control strategy, where predictions of agents are generated actively, so that the computational efficiency is improved than passive approaches. The proposed control strategy is verified by two types of time-varying formations of wheeled mobile robots, and the experimental results show that the proposed control strategy is effective for general time-variant consensus tracking problems of planar multi-agent systems with non-holonomic constraints in local and worldwide networked environments.     

实现战术态势估计的一种多agent计划识别方法

利用目标编群思想描述多agent行动之间的协作关系,建立了一种基于多agent计划识别的战术态势估计模型。分析了计划库的构成及结构层次,给出了一种基于多agent假设的计划识别算法。以一阶谓词逻辑为形式语言,扩展了战术智能规划的一个实例,引入了描述多agent完成同一任务的谓词和算子。对实例的分析说明了基于多agent计划识别的态势估计过程,表明了使用该方法求解态势估计问题的可行性。     

Leader selection for strong structural controllability of single-integrator multi-agent systems

This paper addresses the leader selection problem for strong structural controllability (SSC) of multi-agent systems (MASs). For a path-bud graph, it is proved that only one leader is required to guarantee the SSC of MASs. For a special type of topologies, based on the partition of the topology into disjoint pathes and path-buds, it is proved that the MASs is strongly structurally controllable if the root nodes of the pathes are selected as leaders. For general topologies, an algorithm is provided to determine the agents that can behave as leaders. For some special topologies, the minimum number of leaders guaranteeing the robust strong structural controllability (RSSC) of MASs is also obtained. Two examples are given to verify the effectiveness of the results.     

Multi-agent在油料调拨指挥系统中的应用研究

为了实现信息化战争中军队油料调拨指挥决策的智能化，将multi—agent技术引入到军队油料调拨指挥系统．阐述了建立基于multi—agent军队油料调拨指挥系统的必要性；对基于multi—agent的油料调拨问题求解进行了描述；对基于multi—agent的军队油料调拨指挥系统进行了总体设计，构造了面向油料调拨过程的各类agent及其运行机制；建立了相应的调拨模型和multi—agent模糊关联决策模型；最后阐明了该研究对军队油料调拨指挥决策的实际应用价值．     

多Agent协作的拼配类决策支持系统研究与实现

在分析和获取拼配经验知识的基础上，建立了一种基于Agent协作的拼配类决策支持系统，即在知识和数据表达，以及拼配模型建立的基础上，通过创建控制Agent(CA)和执行Agent(EA)来实现知识与模型结合、计算与推理并行、协作交互控制的分布式处理机制，完全符合实际拼配的要求。文章阐述了系统的构成，知识与数据的表示，拼配算法模型的建立、协作交互处理的流程等，最后给出了系统在出口茶叶拼配中的应用。     

基于自适应SGD-多智能体的防空资源部署优化

针对分布式环境下的战场指挥资源部署存在的效率低、速度慢、无法达到预期战略、数据集过大导致计算资源损耗过大等问题,提出了一种分布式环境下多智能体联盟的指挥控制资源部署优化算法。通过对深度学习中的梯度下降算法进行学习率的改进,将原本设定的学习率改为自适应的学习率,进而对指挥控制资源部署进行多智能体联盟的设计。仿真证明了该算法对此问题具有优越的适应性,可以高效地解决分布式环境下的多智能体联盟的指挥控制资源部署优化问题。     

多Agent诊断系统合作评价策略

多Agent系统提供了分布式和合作问题求解的环境，每个诊断Agent都可以面向各自的知识库进行诊断，提高了诊断系统的可靠性和实时性，但同时也带来了合作评价问题。在介绍多Agent诊断系统结构的基础上，介绍了基于语气理论的合作评价策略，并研究了有互斥故障情况下的合作评价问题，有利于提高多Agent诊断系统的可行性。     

DISTRIBUTED FINITE-TIME χ-CONSENSUS ALGORITHMS FOR MULTI-AGENT SYSTEMS WITH VARIABLE COUPLING TOPOLOGY

<正> This paper considers finite-time χ-consensus problem for a multi-agent system with firstorderindividual dynamics and switching interaction topologies.Several distributed finite-time consensusrules are constructed for multi-agent dynamics in a unified way with the help of Lyapunovfunction and graph theory as well as homogeneity.Time-invariant non-smooth forms of finite-timeneighbor-based controllers are proposed and a numerical example is shown for illustration.     

Event-Triggered Consensus for Discrete-Time Multi-agent Systems with Parameter Uncertainties Based on a Predictive Control Scheme

In this paper, the event-triggered consensus for linear discrete-time multi-agent systems with parameter uncertainties is investigated. The parameter uncertainty is assumed to be normbounded. An event-triggered consensus protocol based on the predictive control method is proposed to make the multi-agent system achieve consensus. And for the design of the consensus protocol, the problem of estimating the control input is transformed into the problem of estimating state differences between agents. Furthermore, the event-triggered consensus protocol proposed in this paper only demands each agent to mornitor its state to determine its event-triggered instants. A sufficient existence condition for the consensus protocol is proposed based on the linear matrix inequality. And a sufficient condition for the nonexistence of the Zeno-like behaviour is also derived. Finally, a numerical example is given to illustrate that the event-triggered consensus protocol proposed in this paper can make the multi-agent system with parameter uncertainties achieve consensus effectively.     

Consensus of Single Integrator Multi-Agent Systems with Unbounded Transmission Delays

This paper investigates the consensus problem of single integrator multi-agent systems with unbounded time-varying transmission delays and fixed directed topology. A distributed controller is proposed taking into consideration the unbounded transmission delays. It is shown that the consensus problem can be solved via the proposed controller under the spanning tree assumption and the nocycle assumption. The authors characterize the no-cycle assumption and prove the consensus of the concerned multi-agent system with an induction procedure. Two simulation examples are provided,one to illustrate the effectiveness of our result and the other to show the necessity of the no-cycle assumption.     

智能虚拟维修环境多Agent 协作机制

针对智能虚拟维修环境中多Agent协同作业求解问题,提出一种基于任务驱动方法的协同虚拟维修训练体系框架,并构建基于该框架下的协作感知-规划-行为（Sense-Plan-Action,SPA）关系模型,在该模型中使用参数化表达方法来量化多Agent 协同作业过程,并将任务求解过程转化为时序信息、属性状态演变、目标决策等多通道框架驱动协同作业的实现,解决了多Agent 协同作业的逻辑关系问题。最后,将该方法应用于轮式工程机械协同虚拟维修仿真过程中,实现了协同虚拟维修可视化,验证了任务驱动方法在协同虚拟训练中的可行性。     

基于多智能体的无人作战防御系统不完全全局规划

不完全全局规划是分布式人工智能协调机制的重要方法,也是解决多智能体间协作协调问题的一种重要方法。本文以无人作战多武器防御系统平台为研究背景,应用对策论和协进化方法以及两者的结合,对多智能体的不完全全局规划作一理论讨论和应用尝试。