Topology Identification of Heterogeneous Networks of Linear Systems

This paper deals with the problem of reconstructing the graph structure of a dynamical network using measured data. This problem is often referred to as topology identification and has received considerable attention in recent literature. Most existing literature focuses on topology identification for networks of single integrators or networks of single-input single-output systems. The aim of this paper is to study topology identification for a more general class of so-called heterogeneous networks, in which the dynamics of the nodes are modeled by general (possibly distinct) linear systems. Our two main contributions are the following. First, we state conditions for topological identifiability, i.e., conditions under which the network topology can be uniquely reconstructed from measured data. Secondly, we develop a topology identification scheme that is based on subspace methods and that is able to reconstruct the network topology for the general class of systems.