Discrete-time frequency response identification method for processes with final cyclic-steady-state

Abstract A new non-parametric process identification method is proposed to obtain the discrete-time frequency response model from the process input and output data. The existing discrete-time Fourier transform approach can be applied to only the case that the initial part and the final part of the process data are zero-steady-state to estimate perfect frequency response data without modeling errors. The proposed method using a new transform can estimate the exact frequency response model from more various process excitation cases including initial-steady-state/final-steady-state and initial-steady-state/final-cyclic-steady-state. It can estimate exact frequency response model because no approximations are used in developing the proposed algorithm. Also, the proposed method can still provide exact model even in the case of static disturbances and sinusoidal disturbances of which the frequencies are multiples of the cyclic-steady-state frequency.