Bias-compensated Least Squares Method in Closed Loop Environment
نویسنده
چکیده
In this paper, a bias-compensated least squares (BCLS) 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. The proposed estimator is unbiased and it does not require the reference input be informative. An iterative redesign of the prefilters is also considered in order to achieve a minimum variance estimator. The proposed BCLS method is applied for the iterative redesign of the prefilters in order to reduce the computational cost.
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