  Fault detection and isolation is an area of engineering dealing with
designing on-line protocols for systems that allow one to identify the
existence of faults, pinpoint their exact location, and overcome them. We
consider the case of multi-agent systems, where faults correspond to the
disappearance of links in the underlying graph, simulating a communication
failure between the corresponding agents. We study the case in which the agents
and controllers are maximal equilibrium-independent passive (MEIP), and use the
known connection between steady-states of these multi-agent systems and network
optimization theory. We first study asymptotic methods of differentiating the
faultless system from its faulty versions by studying their steady-state
outputs. We explain how to apply the asymptotic differentiation to detect and
isolate communication faults, with graph-theoretic guarantees on the number of
faults that can be isolated, assuming the existence of a "convergence assertion
protocol", a data-driven method of asserting that a multi-agent system
converges to a conjectured limit. We then construct two data-driven model-based
convergence assertion protocols. We demonstrate our results by a case study.
