ID PW
 
* Join the Member of ICROS 
* Need your ID or Password?
 
 
 
Subject Keyword Abstract Author
 
 
Time-limited Gramians Based Model Reduction Framework for 1-D and 2-D Systems

Muhammad Imran*, Syeda Fizza Hamdani, and Muhammad Imran
International Journal of Control, Automation, and Systems, vol. 20, no. 11, pp.3540-3548, 2022

Abstract : Gawronski and Juang provide an unstable reduced-order model formulation without a priori error bounds for the original one- and two-dimensional models. Several strategies were put forth for the standard linear discretetime one-dimensional models to guarantee the stability of the reduced-order model over a given time-intervals. These frameworks produce significant truncation mistakes and lack time-domain error-bound expressions. For discrete-time, two-dimensional Gramians models, there are no stability-preserving frameworks that the authors are aware of. This study suggests a Gramian-based model reduction strategy for discrete-time models. One- and two-dimensional discrete-time models can be employed with the framework. The suggested model reduction approach is applied using time-limited Gramians after the discrete-time two-dimensional causal recursive separable denominator models are split into two sub-models (two one-dimensional cascaded models). The framework ensures reduced-order model stability and offers time-domain a priori error-bound expressions for one- and twodimensional models. Comparisons and numerical results demonstrate the usefulness of the proposed framework.

Keyword : "Minimal realization, minimal-rank decomposition, model reduction, time-limited Gramians. "

 
Copyright ⓒ ICROS. All rights reserved.
Institute of Control, Robotics and Systems, Suseo Hyundai-Ventureville 723, Bamgogae-ro 1-gil 10, Gangnam-gu, Seoul 06349, Korea
Homepage http://eng.icros.org | Tel. +82-2-6949-5801 (ext. 3) | Fax. +82-2-6949-5807 | E-mail icros@icros.org