Identification of Continuous-time Transfer Function Models from Non-uniformly Sampled Data in Presence of Colored Noise

Abstract

This paper considers the problem of continuous-time model identification from non-uniformly sampled input-output data, having the measured output corrupted by colored noise. We concentrate on the continuous-time transfer function model identification. A Box-Jenkins model structure is used to describe the system, thus providing independent parameterizations for the plant and the noise. Monte Carlo simulation analysis is also used to illustrate the properties of the proposed estimation method.