  This paper considers the problem of dynamic average consensus algorithm
design for a group of communicating agents. This problem consists of designing
a distributed algorithm that enables a group of agents with communication and
computation capabilities to use local interactions to track the average of
locally time-varying reference signals at each agent. The objective of this
article is to provide an overview of the dynamic average consensus problem that
serves as a comprehensive introduction to the problem definition, its
applications, and the distributed methods available to solve them. Our primary
intention, rather than providing a full account of all the available
literature, is to introduce the reader, in a tutorial fashion, to the main
ideas behind dynamic average consensus algorithms, the performance trade-offs
considered in their design, and the requirements needed for their analysis and
convergence guarantees.
