Model-Free Formation-Containment Control for Nonlinear MASs with Output Saturation and Data Dropouts

This paper explores the formation-containment control problem for nonlinear multi-agent systems with output saturation and data dropouts. The prior paradigm usually addresses the two issues separately based on agent models. To circumvent unknown dynamics and solve these two problems simultaneously, a distributed model-free adaptive formation-containment control (DMFA-FCC) method is formulated. Firstly, the data mapping of agents with output saturation information is established by the locally dynamic linearization technique. Consider the data dropout process follows the Bernoulli distribution, and a backward data compensation mechanism is integrated into the controller. Secondly, the convergence analysis conditions of the formulated method are provided by the nature of irreducible sub-stochastic matrices. Finally, experiments verify the DMFA-FCC method.