Structure Identifiability of an NDS With LFT Parametrized Subsystems

Requirements on subsystems have been made clear in this paper for a linear time invariant (LTI) networked dynamic system (NDS), under which subsystem interconnections can be estimated from external output measurements. In NDS, may distinctive dynamics, and are arbitrary. It is assumed that matrices of each depend its (pseudo) first principle parameters (FPPs) through fractional transformation (LFT). has proven if subsystem, the transfer function matrix (TFM) internal inputs to outputs full normal column rank (FNCR), while TFM row (FNRR), then structure NDS identifiable. Moreover, some particular situations like there no direct information transmission an input necessary sufficient condition established identifiability. A valued polynomial (MVP) based equivalent further derived, depends affinely FPPs independently verified subsystem. From condition, conditions obtained both dynamics FPPs, using Kronecker canonical form (KCF) pencil.