  The problem of controlling complex networks is of interest to disciplines
ranging from biology to swarm robotics. However, controllability can be too
strict a condition, failing to capture a range of desirable behaviors.
Herdability, which describes the ability to drive a system to a specific set in
the state space, was recently introduced as an alternative network control
notion. This paper considers the application of herdability to the study of
complex networks under the assumption that a positive system evolves on the
network. The herdability of a class of networked systems is investigated and
two problems related to ensuring system herdability are explored. The first is
the input addition problem, which investigates which nodes in a network should
receive inputs to ensure that the system is herdable. The second is a related
problem of selecting the best single node from which to herd the network, in
the case that a single node is guaranteed to make the system is herdable. In
order to select the best herding node, a novel control energy based herdability
centrality measure is introduced.
