This article investigates data-driven distributed bipartite formation issues for discrete-time multi-agent systems with communication constraints. We propose a quantized data-driven distributed bipartite formation control approach based on the plant’s quantized and saturated information. Moreover, compared with existing results, we consider both the fixed and switching topologies of multi-agent systems with the cooperative-competitive interactions. We establish a time-varying linear data model for each agent by utilizing the dynamic linearization method. Then, using the incomplete input and output data of each agent and its neighbors, we construct the proposed quantized data-driven distributed bipartite formation control scheme without employing any dynamics information of multi-agent systems. We strictly prove the convergence of the proposed algorithm, where the proposed approach can ensure that the bipartite formation tracking errors converge to the origin, even though the communication topology of multi-agent systems is time-varying switching. Finally, simulation and hardware tests demonstrate the effectiveness of the proposed scheme.

中文翻译：

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具有通信约束的多智能体系统的基于数据的二方编队控制

本文研究了具有通信约束的离散时间多智能体系统的数据驱动的分布式二分形成问题。我们提出了一种基于植物的量化和饱和信息的量化数据驱动的分布式二分形成控制方法。此外，与现有结果相比，我们考虑了具有合作竞争相互作用的多智能体系统的固定拓扑和交换拓扑。我们利用动态线性化方法为每个代理建立了时变线性数据模型。然后，利用每个智能体及其邻居的不完整输入和输出数据，我们构造了所提出的量化数据驱动的分布式二分编队控制方案，而不使用多智能体系统的任何动态信息。我们严格证明了所提出算法的收敛性，其中所提出的方法可以确保二分编队跟踪误差收敛到原点，即使多智能体系统的通信拓扑是时变切换的。最后，仿真和硬件测试证明了该方案的有效性。