2-stage approach for continuous time identification using step response estimates

This paper presents the 2-stage identification approach. The first stage is the identification of the system step response from the experimental data using the frequency sampling filter approach. This first stage is also referred as data compression stage in which the raw data will be analyzed in order to obtain a parameter that describes the empirical model of the analyzed data. The second stage is the identification of a continuous time state space model using subspace methods from the identified step response. The performance of the proposed approach is evaluated to identify the simulated systems and the real system of magnetic bearing apparatus.