Fast, Analytical Method for Structured Identification of SISO RC-Ladder-Type Systems

Structured system identification often requires solving optimization problems that are not deterministic in computation time and may converge to a local optimum. For the case of systems that can be represented as a SISO “RC-ladder” impedance network, this brief presents a closed-form algorithm that can determine the structured state-space matrices and extract the parameters from an arbitrarily transformed system, such as that produced by subspace system identification. This algorithm relies on a modified version of the Lanczos tridiagonalization process and the solving of a least squares problem with dimension equal to the system order. It is fast, deterministic, and successful for systems of low to moderate order. Practical applications include network synthesis, thermal model identification, and distributed sensing reconstruction, where exact RC parameter values must be identified from data.