An indirect method for transfer function estimation from closed loop data

An indirect method is introduced that is able to consistently estimate the transfer function of a linear plant on the basis of data obtained from closed loop experiments, even in the situation when the model of the noise disturbance on the data is not accurate. The primary interest is not the consistent identification of the system, but the gathering of a good approximation of its input-output transfer function. The method allows approximate identification of the open loop plant with an explicit and tunable expression from the bias distribution of the resulting model.<>