Neuro-adaptive leaderless consensus of fractional-order multi-agent systems

Abstract

Leaderless consensus control problem of fractional-order multi-agent systems (FOMASs) with unknown nonlinearities and unknown external disturbances is investigated in this paper. Firstly, based on neural networks, an adaptive control protocol with integer-order dynamics is proposed to approximate the unknown nonlinearities, which is easy to implement in reality. And then, a novel auxiliary Lyapunov function which contains Riemman–Liouvile fractional-order integral is first constructed to verify the effectiveness of the designed control protocol. Moreover, the convergence analysis of FOMASs is finished by taking the Barbalat lemma for the first time. Finally, theoretical results are demonstrated by several numerical simulations.