Cooperative Adaptive Output Regulation for Unknown Multi-agent Systems with Nonidentical Relative Degrees
Ying Zhang, Youfeng Su, Xinghu Wang · 2018
In this paper, we present a novel universal adaptive output feedback control for the cooperative output regulation problem of linear multi-agent systems. The agent plant is general in the sense that those interesting practical issues such as unknown dynamics, direct network graph, and nonidentical relative degree agents are taken into account simultaneously. The obtained controller consists of the reduced-order observer, the internal model, as well as the adaptive control law, all of which are shown to be fully distributed. It is of interest to see that, in our recursive design, each agent does not need to estimate the unknown parameters caused by the neighbors, giving rise to a merely two-dimensional adaptive law with quite a simple structure. It is also this feature that our design has the capability of handling the agents with arbitrary nonidentical high relative degrees.