Book Contribution

Continuous-Time Model Identification Using Spectrum Analysis with Passivity-Preserving Model Reduction

Rolf Johansson

Abstract

A continuous-time model identification approach using spectrum analysis with passivity-preserving model reduction is presented. Based on discrete-time input-output data, the two-step algorithm provides an intermediate high-order continuous-time state-space model by means of linear regression. A final passivity-preserving step of model reduction provides a continuous-time low-order state-space model and noise model. Matrix relationships of positive-real properties and stability are provided.

Keywords

Continuous-time Identification, Model Reduction, Passivity, Spectrum Analysis


In : Identification of Continuous-time Models from Sampled Data, Springer-Verlag, London, March 2008. H. Garnier, L. Wang (Eds.), pp. 393-406.