Distributed data-driven consensus control of multi-agent systems under switched uncertainties

Cooperative control of multi-agent systems (MASs), particularly consensus control, has gained significant attention in the last two decades, thanks to the rapid and sustained development of distributed and networked systems. In this paper, we present some new results focused on consensus control of a set of unknown linear MASs (whose system matrices are unknown) under unknown switched uncertainties, with an emphasis on distributed data-driven controllers. The proposed controller is end-to-end, designed by solving two data-based semi-definite programs (SDPs), which adjust to the changes of the uncertainty modes. Our approach achieves asymptotic consensus of the MAS provided that the switching is slow enough and the uncertainty is small. We illustrate the effectiveness of our proposed method through a numerical example.