Statistical Analysis of Least-Squares Identification for Robust Control Design: Output Error Case With Affine Parametrization

Precise, finite-data statistical propereties are determined using a least-square estimator baed on an output error model with an affine parameter representation where the true system is of output error form, but is not in the model set. The purpose of the analysis is to show the effect of unmodeled dynamics on the resulting closed-loop system designed on the basis of the estimated transfer function. This simple problem set-up is prototypical of the interplay between system identification and robust control design.