This paper investigates the containment problem for fractional-order multi-agent systems (FOMASs) with unknown nonlinear functions over a directed communication topology. To solve this problem, the unknown functions are emulated by radial basis function neural networks. Then, we design novel distributed containment algorithms with adaptive control gainsand deduce some sufficient conditions. By taking the properties of the Mittag–Leffler function, the convergence analysis is finished. Finally, simulation examples show the effectiveness of the obtained theoretical results.

中文翻译：

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使用神经网络的分数阶多智能体系统的分布式包含控制

本文研究了在有向通信拓扑上具有未知非线性函数的分数阶多智能体系统 (FOMAS) 的包含问题。为了解决这个问题，我们用径向基函数神经网络来模拟未知函数。然后，我们设计了具有自适应控制增益的新型分布式包含算法，并推导出了一些充分条件。通过获取 Mittag-Leffler 函数的性质，完成了收敛性分析。最后通过仿真算例验证了所得理论结果的有效性。