Iterative Learning Control for Multi-Agent Systems Over Unknown Fading Networks

This paper studies the consensus problem for multi-agent systems over unknown fading networks. The directed graph is used to describe the communication between agents. The fading process is modeled by a random variable multiplied to the original signal. It is the first time to study the effect of unknown fading networks in a distributed structure. An iterative estimation is presented to obtain the statistical property of fading networks. Moreover, a distributed learning control scheme is proposed to establish the learning consensus performance. The input errors for all agents are strictly proved convergent to zero in the mean-square sense. In the end, numerical simulations are presented to verify the proposed scheme.