State-space model identification using input and output data with steady state values zeroing multiple integrals of output error

Abstract

This study proposes a new deterministic off-line identification method that obtains a state-space model using input and output data with steady state values. This method comprises two methods: zeroing the 0 » N -tuple integral values of the output error of single-input single-output transfer function model [1] and Ho-Kalman’s method [2]. Herein, we present a new method to derive a matrix similar to the Hankel matrix using multi-input and multi-output data with steady state values. State space matrices A, B, C and D are derived from the matrix by the method shown in reference [2]. This method’s utility is that the derived state-space model is emphasized in the low frequency range under certain conditions. Numerical simulations of multi-input multi-output system identification are illustrated.