Relative-error H∞ identification fromautocorrelation data-a stochastic realization method

A variant of the balanced stochastic truncation (BST) method for approximated realization of power spectrum matrices is shown to form the basis for an identification procedure that is well-suited to the task of determining relative-error-bounded approximate plant models for use in control design from input-output cross correlation data. Central to the theory is a novel L_∞-norm bound on the relative-error between an exact realization of the data and BST approximate realization