Finite-time consensus of networked Lipschitz nonlinear agents under communication constraints

In this paper, we study the finite-time consensus problem for a team of networked Lipschitz nonlinear agents under communication constraints, where each agent has a limited sensing range. Because the induced interaction graph is typically state-dependent and dynamic, we propose a distributed nonlinear control algorithm that is capable of preserving the initial interaction patterns. By using tools from nonsmooth analysis, we present conditions on the initial interaction graph and the control gain such that finite-time consensus can be reached. More specifically, an upper bound of the convergence time is derived via a two-step analysis.