This article considers the problem of finite-time consensus for nonlinear multiagent systems (MASs), where the nonlinear dynamics are completely unknown and the output saturation exists. First, the mapping relationship between the output of each agent at the terminal time and the control input is established along the iteration domain. By using the terminal iterative learning control method, two novel distributed data-driven consensus protocols are proposed depending on the input and output saturated data of agents and its neighbors. Then, the convergence conditions independent of agents' dynamics are developed for the MASs with fixed communication topology. It is shown that the proposed data-driven protocol can guarantee the system to achieve two different finite-time consensus objectives. Meanwhile, the design is also extended to the case of switching topologies. Finally, the effectiveness of the data-driven protocol is validated by a simulation example.

中文翻译：

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具有输出饱和的非线性多主体系统的数据驱动终端迭代学习共识。

本文考虑了非线性多主体系统（MAS）的有限时间共识问题，其中非线性动力学完全未知，并且存在输出饱和。首先，沿着迭代域建立终端时间每个代理的输出和控制输入之间的映射关系。通过使用终端迭代学习控制方法，根据代理及其邻居的输入和输出饱和数据，提出了两种新颖的分布式数据驱动共识协议。然后，针对具有固定通信拓扑的MAS，开发了与代理动力学无关的收敛条件。结果表明，提出的数据驱动协议可以保证系统达到两个不同的有限时间共识目标。与此同时，该设计还扩展到交换拓扑的情况。最后，通过仿真示例验证了数据驱动协议的有效性。