Model Reduction for Aperiodically Sampled Data Systems * *This work was partially supported by ESTIREZ project of Region Nord-Pas de Calais, France and by ANR project ROCC-SYS (ANR-14-CE27-0008).

Abstract

Abstract Two approaches to moment matching based model reduction of aperiodically sampled data systems are given. In certain cases, such systems can be represented by discrete-time linear switched (LS) state space (SS) models. One of the approaches investigated in the paper is to apply model reduction by moment matching on the linear time-invariant (LTI) plant model, then compare the responses of the LS SS models acquired from the original and reduced order LTI plants. The second approach is to apply a moment matching based model reduction method on the LS SS model acquired from the original LTI plant; and then compare the responses of the original and reduced LS SS models. It is proven that for both methods, as long as the original LTI plant is stable, the resulting reduced order LS SS model of the sampled data system is quadratically stable. The results from two approaches are compared with numerical examples.