  This paper reports a robust scheme for topology identification and control of
networks running on linear dynamics. In the proposed method, the unknown
network is enforced to asymptotically follow a reference dynamics using the
combination of Lyapunov based adaptive feedback input and sliding mode control.
The adaptive part controls the dynamics by learning the network structure,
while the sliding mode part rejects the input uncertainty. Simulation studies
are presented in several scenarios (detection of link failure, tracking time
varying topology, achieving dynamic synchronization) to give support to
theoretical findings.
