Abstract
In this paper, a bias-compensated least squares method in the closed loop environment is proposed. It is assumed that the observation noise is a white gaussinan signal while there are no process noises. It is also assumed that the plant is controlled by a linear time invariant controller and that the closed loop system is asymptotically stable. It is shown that the asymptotic bias of the least squares estimate in the closed loop environment is represented as a difference between the parameter of the prefilter and that of an “opetimal prefilter” and that the propsed bias-compensated least squares estimate is consistent.
