Fault Detection and Isolation in Linear Heterogeneous Multi-Agent Networks

Detection and isolation of faulty behaviours in multi-agent dynamical networks under cooperative control laws is of paramount importance to secure that the network operation is not jeopardized by the failing of one or more of its nodes. The paper investigates under which conditions the fault detectability and isolability (FDI) properties of the individual agent are improved because of the information sharing with other agents in the network. Relying on the parity space method and focusing the analysis on linear heterogeneous dynamical systems two main contributions are achieved: (i) the sharing of information through the cooperative control law does not improve the FDI properties of the individual agents; (ii) the presence of relative measurements among the agents results in improved fault detection and isolation capabilities the multi-agent system under the assumption of a strongly connected network.