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目前,相互协作的多智能体完成跟踪目标时通常需要连续的通讯,这种通讯包括至少一个智能体与被跟踪目标之间的通讯和相邻智能体之间的通讯。然而在实际络中,随着多智能体数量的增加以及节点之间紧密的联系,会导致这种网络通讯拥堵,不易实现。因此,提出了一种新型的基于事件驱动策略的多智能体移动目标跟踪算法,当且仅当被跟踪的目标在某个智能体的感测范围内时和智能体之间的状态差超过某个预定的阈值时,触发事件驱动函数,施加相应的控制策略。然后通过构建李亚普诺夫函数对该算法进行分析,证明了算法的有效性。最后,对一个由200个智能体组成的网络,其跟踪目标为所有智能体的平均值和感测范围分别为0.5和5.5,事件驱动函数触发的次数分别为538和5201。仿真表明系统均能完成跟踪任务,这样显著减少通讯量,克服了拥堵现象,而且容易实现。
Currently, interoperable multi-agent usually needs continuous communication when it accomplishes the goal of tracking. This communication includes the communication between at least one agent and the tracked target and the communication between the neighboring agents. However, in the real network, with the increase of the number of multi-agent and the close connection between the nodes, this kind of network communication will be jammed and difficult to be realized. Therefore, a new event-driven strategy based multi-agent moving target tracking algorithm is proposed. If and only if the target being tracked is within the sensing range of an agent and the state difference between the agent and the agent exceeds a certain A predetermined threshold, the event-driven function is triggered and the corresponding control strategy is applied. Then, the algorithm is analyzed by constructing Lyapunov function, which proves the effectiveness of the algorithm. Finally, for a network composed of 200 agents, the tracking goal is that the mean and sensing range of all agents are 0.5 and 5.5 respectively, and the number of event-driven functions is 538 and 5201 respectively. Simulation shows that the system can complete the tracking task, thus significantly reducing the amount of traffic, to overcome the congestion, and easy to implement.