Distributed nonconvex input-constrained consensus of multi-agent systems under sampled-data settings and communication delays

This paper explores the nonconvex input-constrained consensus problem of multi-agent systems under sampled-data settings, switching graphs and communication delays. A sampled-data based consensus control algorithm is developed for systems with nonconvex input-constrained second-order dynamic. To address the nonlinearities arising from the coupling of nonconvex input constraints and sampled-data setting, the scaling factors are applied to convert the nonconvex input-constrained system into a time-varying linear form. Then, an inductive approach utilising the lower bounds of these scaling factors is developed to analyse the system's convexity. It is verified that the nonconvex input constrained consensus under sampled-data settings, switching graphs, and communication delays can be achieved. Finally, the theoretical conclusions are verified through numerical examples.