  Synchronization is a crucial phenomenon in many natural and artificial
complex network systems. Applications include neuronal networks, formation
control and coordination in robotics, and frequency synchronization in
electrical power grids. In this paper, we propose the use of a distributed
discontinuous coupling protocol to achieve convergence and synchronization in
networks of non-identical nonlinear dynamical systems. We show that the
synchronous dynamics is a solution to the average of the nodes' vector fields,
and derive analytical estimates of the critical coupling gains required to
achieve convergence. Numerical simulations are used to illustrate and validate
the theoretical results.
