Blind Local Identification of Large-Scale Networked Systems

For a large-scale networked system, it is computationally prohibitive to conduct the global network identification on a single computational platform. To deal with this problem, the global network is split into a number of local subnetworks and the global identification is to be accomplished by local identifications of subnetworks in parallel. However, due to the couplings or unmeasurable interconnections among the systems operating in a large-scale network, the local identification is inherently a blind identification problem, which is similar to that investigated in Chap. 9. However, due to specific properties of the unmeasurable interconnection signals, a numerically reliable subspace identification approach will be developed by subsequently estimating the unknown inputs and the local state-space models.