  This paper addresses distributed average tracking for a group of
heterogeneous physical agents consisting of single-integrator,
double-integrator and Euler-Lagrange dynamics. Here, the goal is that each
agent uses local information and local interaction to calculate the average of
individual time-varying reference inputs, one per agent. Two nonsmooth
algorithms are proposed to achieve the distributed average tracking goal. In
our first proposed algorithm, each agent tracks the average of the reference
inputs, where each agent is required to have access to only its own position
and the relative positions between itself and its neighbors. To relax the
restrictive assumption on admissible reference inputs, we propose the second
algorithm. A filter is introduced for each agent to generate an estimation of
the average of the reference inputs. Then, each agent tracks its own generated
signal to achieve the average tracking goal in a distributed manner. Finally,
numerical example is included for illustration.
