基于相对方位信息和单间距测量的多智能体编队协同控制

由多个载体组成的多智能体系统对复杂环境具有更高的适应性,能够完成传统单个载体无法完成的任务。针对多智能体编队集结与队形移动跟踪问题,提出了一种改进的多智能体编队协同控制新算法。首先,以拒止环境下跟随智能体仅能通过光学传感器测量相对方位信息为任务背景,针对"领导者——第一跟随者"结构的多智能体编队,提出了基于相对方位信息与单间距测量的控制器,使得第一跟随者智能体可以追随移动的领导者智能体,并且可以通过改变与领导者智能体的间距对编队整体队形进行缩放控制。其次,提出一种了改进的分布式控制律,使得其他跟随者智能体可以仅通过两个相对方位信息完成编队飞行。然后,根据Lyapunov第二方法,构建了系统的能量函数,验证了所提出算法的稳定性。最后,通过数值仿真实验对所提算法进行了验证。仿真结果表明,基于该控制律多智能体系统能够完成编队集结、队形缩放和编队飞行的任务。     

基于多Agent的机身外形优化模型

提出了一个基于多Agent系统的机身外形优化模型,并将其用于飞机概念设计阶段的多学科优化中。该模型继承了多Agent系统的自主、协作等优点,并且结合了机身段和机身剖面的建模方法。提出并定义了不同类型的Agent及其功能,对各类Agent选用了不同的协调方式及协调规则。作为对模型的验证,针对一个战斗机方案多学科优化设计的算例,给出了机身外形中各Agent的协调过程。优化结果表明这一模型在优化过程中能有效地减少机身的优化变量,缩短计算时间。同时,由于各Agent之间的自主协调避免了复杂机身外形在优化中产生扭曲,从而增加了可行解的数量。     

基于终端滑模控制的四旋翼无人机编队控制

本文以四旋翼无人机为研究对象,基于终端滑模控制技术,实现了四旋翼无人机系统的编队飞行控制。在构建四旋翼无人机数学模型的基础上,为每架四旋翼无人机设计了广义误差状态,基于广义误差状态提出编队控制目标。为实现编队控制目标,设计了基于终端滑模控制的编队控制器,最终所有四旋翼无人机的广义误差状态收敛到零时即实现期望的编队队形,进一步结合有限时间稳定性理论给出了上述编队控制器有限时间稳定性证明。最后用一个仿真实例验证了所提出算法的有效性,并将本文提出的控制器与基于线性滑模控制的控制器进行对比,实验证明所提出的控制算法具有更好的编队控制效果。     

基于多智能体深度强化学习的多星观测任务分配方法

为应对多星环境中复杂多约束条件下的任务分配场景,提出一种多星自主决策观测任务分配算法,该算法采用基于集中式训练、分布式执行的多智能体深度强化学习算法。通过这种方式训练后的卫星智能体,即使在没有中心决策节点或通信受限的情况下,仍具有一定的自主协同能力及独立实现多星观测任务的高效分配能力。     

基于多Agent的电力调度自动化系统

介绍了一个电力调度自动化系统的功能组成与拓扑结构,提出了一种基于多Agent技术的软件设计方法,该方法利于集成性、开放性、复用性软件结构设计,并利用黑板进行消息发布、资源管理Agent进行任务流分解、协调Agent进行各Agent之间的合作、成员Agent完成子任务的执行.定义了系统中的资源与元任务.最后,基于JADE平台,介绍了该系统的实现方法.多Agent技术应用于SCADA系统,将利于复杂系统的开放组合.     

基于多Agent的舰载机弹射起飞仿真层次模型(英文)

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the pro     

基于分布式自适应的多智能体容错一致性控制

针对"领航者-跟随者"的多智能体编队，由于领航者系统出现故障引起编队通讯中断而不能完成任务的问题，提出了一种基于一致性理论的分布式自适应控制方法，用于解决该问题。首先，以一个位于顶点的智能体作为领航者，其余3个位于同一条线上的智能体作为跟随者，由此所构成的三角形编队作为被控对象。其中，领航者速度方向作为编队的前行方向，跟随者位于领航者之后。其次，基于图论，对智能体局部信息参数进行分布式自适应更新，并设计分布式自适应控制律，用于弥补多智能体编队中领航者故障所造成的影响。同时，根据相邻智能体的局部信息，设计整体分布式自适应容错控制律，进一步通过构建合理的Lyapunov函数，证明所设计控制器的稳定性，以及"领航者-跟随者"之间相对横向以及相对纵向的距离误差均收敛于固定常数。最后，仿真验证表明：所提出的自适应控制方法具有良好的鲁棒性，这也为工程实践提供了理论依据。     

基于Multi-Agent信息融合的机载设备故障诊断系统研究

尝试构建基于MuIti-Agent信息融合技术的机载设备故障诊断系统,并对该诊断系统的体系结构、运行过程和关键技术做了详细说明.     

Formation tracking control for time-delayed multi-agent systems with second-order dynamics

In this paper, formation tracking control problems for second-order multi-agent systems (MASs) with time-varying delays are studied, specifically those where the position and velocity of followers are designed to form a time-varying formation while tracking those of the leader. A neigh-boring relative state information based formation tracking protocol with an unknown gain matrix and time-varying delays is presented. The formation tracking problems are then transformed into asymptotically stable problems. Based on the Lyapunov-Krasovskii functional approach, condi-tions sufficient for second-order MASs with time-varying delays to realize formation tracking are examined. An approach to obtain the unknown gain matrix is given and, since neighboring relative velocity information is difficult to measure in practical applications, a formation tracking protocol with time-varying delays using only neighboring relative position information is introduced. The proposed results can be used on target enclosing problems for MASs with second-order dynamics and time-varying delays. An application for target enclosing by multiple unmanned aerial vehicles (UAVs) is given to demonstrate the feasibility of theoretical results.