  Several algorithms in prior literature have been proposed which guarantee
consensus of normally behaving agents in a network that may contain
adversarially behaving agents. These algorithms guarantee that the consensus
value lies within the convex hull of initial normal agents' states, with the
exact consensus value possibly being unknown. In leader-follower consensus
problems however, the objective is for normally behaving agents to track a
reference state that may take on values outside of this convex hull. In this
paper we present methods for agents in time-varying graphs with discrete-time
dynamics to resiliently track a reference state propagated by a set of leaders
despite a bounded subset of the leaders and followers behaving adversarially.
Our results are demonstrated through simulations.
