New impulse (noncausality) test for descriptor systems by Mobius-transformation

Descriptor systems (DSs) are usually used to model very-large-scale integration (VLSI) circuit systems and multibody dynamics macromodeling. The analysis of DSs, however, is much more complicated than linear time-invariant (LTI) systems due to the poles at infinity. Mȯbius transformation (MT) provides a way to transform poles at infinity to finite poles and largely facilitates the reuse or adaptation of the standard techniques for LTI system to analyze DSs. Nonetheless, MT is well known in the literature and its potential use is currently less appreciated in the analysis of DSs. This paper gives a new way to the impulse (noncausality) test using the properties of the transformed LTI systems by MT. Moreover, the applications to the analysis of controllability, observability and regularity are given. Numerical examples are included to show the effectiveness of the proposed method. © 2012 Chinese Assoc of Automati.published_or_final_versio

Optimal model reduction of discrete-time descriptor systems

An optimal model reduction method is presented to obtain stable reduced-order models for discrete-time descriptor systems. A parametrization based on the bilinear Routh approximation of linear normal discrete-time systems is used to parametrize the causal subsystems of the reduced-order models. The expressions for the error and its gradient are explicitly given. They are then employed to solve an unconstrained optimization problem for the model reduction problem. The descriptor system structure is preserved in the reduced-order models.link_to_subscribed_fulltex