基于事件驱动的异构多智能体系统同步控制研究

The synchronization problem of multi-agent systems has attracted considerable attention in systems and control community, due to its application to a wide range of problems, including sensor networks, rendezvous, formation control and flocking control. The performances of the agents can be modified by a control law, to perform collective behaviors, such as to reach synchronization about relevant variables of interest. The agents exchange information through a communication graph, which can induce time delay and packet loss due to the limitation of wireless network. In order to reduce the induced uncertainties, we adopt the event-triggering function to design the distributed control law. The event-triggered algorithm can reduce the energy consumption of network and the update frequency of controller. The dynamics of individual agents in the network can be identical or non-identical. In a heterogeneous network of non-identical agents, output synchronization among all agents can be achieved via the theory of output regulation.

多智能体系统具有广泛的应用，例如：传感器网络、机器人编队和飞行器编队等等。多智能体系统的同步控制问题是通过设计控制律来使得多智能体系统达到集群行为，使得控制变量达到一致。多智能体之间通过网络来交换信息，受网络带宽和能量的限制，数据在传输过程中会发生时滞和丢包的现象。为了减少网络诱导不稳定因素，可以依据系统信息设计相应的事件驱动条件来进行时变采样控制。这种事件驱动算法能够降低能量消耗和控制器的更新频率。进一步，单个智能体的动态系统描述可以是异构的。在异构多智能体系统中，可以设计基于事件驱动的输出控制器来使得所有智能体的输出达到同步。

异构多智能体系统包含一组相互作用的异构子智能体。基于网络拓扑结构，子智能体能够相互交换信息并生成相应的分布式控制律以达到集群行为。本项目针对异构多智能体在信息交互的过程中存在的网络时滞、数据丢包、动态模型中的参数不确定性等问题，开展了基于系统信息的事件驱动同步控制研究、基于分层结构的事件驱动同步控制研究、基于自适应参考生成器的事件驱动同步控制研究。基于以上研究，解决了多智能体系统中节点数据传输时滞的问题，设计带有不确定主智能体的事件驱动同步控制策略较少了控制器更新频率，设计鲁棒输出调节控制器解决了节点动态描述的异构性参数不确定性，解决了多智能体系统中节点动态描述存在不确定性的问题。