  This paper addresses distributed average tracking of physical second-order
agents with nonlinear dynamics, where the interaction among the agents is
described by an undirected graph. In both agents' and reference inputs'
dynamics, there is a nonlinear term that satisfying the Lipschitz-type
condition. To achieve the distributed average tracking problem in the presence
of nonlinear term, a non-smooth filter and a control input are designed for
each agent. The idea is that each filter outputs converge to the average of the
reference inputs and the reference velocities asymptotically and in parallel
each agent's position and velocity are driven to track its filter outputs. To
overcome the nonlinear term unboundedness effect, novel state-dependent time
varying gains are employed in each agent's filter and control input. In the
proposed algorithm, each agent needs its neighbors' filters outputs besides its
own filter outputs, absolute position and absolute velocity and its neighbors'
reference inputs and reference velocities. Finally, the algorithm is simplified
to achieve the distributed average tracking of physical second-order agents in
the presence of an unknown bounded term in both agents' and reference inputs'
dynamics.
