A Subspace Identification of Continuous-Time Systems usingδ-Operator Model

Abstract

In this paper we derive a subspace-based state-space identification method for continuous-time systems. By using δ-operator [15], we transform the continuous-time system to the discrete-time δ-operator state-space model which converges to the original continuous-time model as the sampling period goes to zero. Then we obtain the estimates of system matrices by applying some well-known subspace identification methods such as MOESP [2] to the discrete-time δ-operator state-space model. Numerical examples are included to show the effectiveness of the proposed method.