An Eecient Frequency Domain State-space Identiication Algorithm: Robustness and Stochastic Analysis 33rd Cdc

In this paper we present a novel algorithm for identifying linear time-invariant discrete time state-space models from frequency response data. The algorithm is non-iterative and exactly recovers a true system of order n, if n + 2 noise-free uniformly spaced frequency response measurements are given. Analysis show that if the measurements are perturbed with errors upper bounded by the identiication error will be upper bounded by and hence the algorithm is robust. An asymptotic stochastic analysis show, under weak assumptions, that the algorithm is consistent if the measurements are contaminated with noise. In a companion paper the algorithm is applied to real data with promising results.