Detection filter design for homogeneous multi-agent networks

Abstract

A class of large-scale systems with decentralized information structures such as multi-agent systems can be represented by a linear system with a generalized frequency variable. In these models agents are modelled through a strictly proper SISO state space model while the supervisory structure, representing the information exchange among the agents, is represented via a linear state-space model. In this paper the fundamental problem of residual generation, as a basic detector filter design task, is solved in the context of homogeneous multi-agent networks. In order to reduce the dependence of the filter on the particular agent and to exploit the inherent informational structure of the network system the same local-global structure is imposed to the filter as of the original system. It is shown that a stable detection filter can be designed if the same structural conditions are fulfilled as in the unstructured LTI case.