  This paper studies the distributed average tracking problem for multiple
time-varying signals generated by linear dynamics, whose reference inputs are
nonzero and not available to any agent in the network. In the edge-based
framework, a pair of continuous algorithms with, respectively, static and
adaptive coupling strengths are designed. Based on the boundary layer concept,
the proposed continuous algorithm with static coupling strengths can
asymptotically track the average of multiple reference signals without the
chattering phenomenon. Furthermore, for the case of algorithms with adaptive
coupling strengths, average tracking errors are uniformly ultimately bounded
and exponentially converge to a small adjustable bounded set. Finally, a
simulation example is presented to show the validity of theoretical results.
