Deep Luenberger observer-based consistency tracking for nonlinear heterogeneous multi-agent systems with uncertain drift dynamics

Abstract

In recent years, multi-agent systems (MASs) technology, represented by swarms of unmanned aerial vehicles (UAVs), has been continuously developed and become a hot topic in academic research. Combining the theory of deep learning (DL) and Luenberger observer, this paper puts forward the tracking control problem for the nonlinear heterogeneous MASs with uncertain drift dynamics. Concretely, a novel class of deep Luenberger observer (DLO) is constructed for state estimation and a novel deep robust controller (DRC) is designed based on the proposed DLOs. Finally, a numerical simulation demonstrates that the proposed methodology is valid, more general and performs better compared to traditional robust control methods.