State-space Model Identification Using Input and Output Data with Steady State Values

Abstract

In this paper, we propose a new deterministic off-line identification method that delivers a state-space model by using input and output data with steady state values. This method combines the method zeroing the 0N-tuple integral values of output error of single-input single-output transfer function model and Ho-Kalman's method. The feature is that this method can identify by using step responses and, consequently, this is suitable for a mechanical system identification in which persistent fluctuations are unacceptable. Numerical simulations of multi-input multi-output system identification are illustrated and the practicability is verified by application to a pneumatic two link arm system.