Bias Compensated State Space Identification Method in Closed Loop Environment

A method of bias compensation in subspace identification method in closed loop environment is proposed. The noise is assumed to be a 0 mean colored noise and is assumed to be uncorrelated with the reference input. The covariance matrix of the noise is estimated directly from the residuals instead of estimating the noise model. The proposing method becomes an iterative algorithm and it is analyzed that the proposing method achieves 2nd order convergence.