Iterative Learning Consensus Tracking of Fractional-Order Multi-Agent Systems with Non-Identical Delays

Abstract

This paper considers the consensus tracking problem of the fractional-order multi-agent systems (FOMASs) subject to both external disturbances and non-identical information processing time delays. For the leader-following FOMASs including one leader and multiple followers, a distributed fractional-order iterative learning consensus protocol is proposed by using the neighbors' information. By selecting the suitable variables, the controlled FOMASs can be rewritten as a two-dimension dynamical system, thereby the consensus control problem is transformed into the stabilization problem of the two-dimension dynamical system, and the sufficient condition of consensus is derived. A numerical example is presented to verify the effectiveness of the proposed method.