  In this paper, we present new results on consensus for continuous-time multi-
agent systems. We introduce the assumptions of persistent connectivity of the
interaction graph and of slow divergence of reciprocal interaction weights.
Persistent connectivity can be considered as the counterpart of the notion of
ultimate connectivity used in discrete- time consensus protocols. Slow
divergence of reciprocal interaction weights generalizes the assumption of
cut-balanced interactions. We show that under these two assumptions, the
continuous-time consensus protocol succeeds: the states of all the agents
converge asymptotically to a common value. Moreover, our proof allows us to
give an estimate of the rate of convergence towards the consensus. We also
provide two examples that make us think that both of our assumptions are tight.
