A Subspace Identification of δ-Operator State-Space Model

Abstract

This paper derives a subspace identification algorithm for a δ-operator state-space model by using the methods due to Moonen et al. [11], [12], [21]. Since the δ-operator model converges to a continuous-time model as the sampling interval goes to zero, the algorithm obtained is applicable to the identification of continuous-time medels. A method of computing the state vector from the block Hankel matrix is developed. Simulation studies show the present algorithm provides good results for the case of a low N/S ratio. Improvement of the algorithm for the case of a higher N/S ratio remains to be done.