Distributed containment control of fractional‐order multi‐agent systems using neural networks

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.