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Development of time-limited model reduction technique for one-dimensional and two-dimensional systems with error bound via balanced structure.
- Source :
-
Journal of the Franklin Institute . Aug2022, Vol. 359 Issue 12, p6438-6466. 29p. - Publication Year :
- 2022
-
Abstract
- In this article, the two-dimensional model is decomposed into two one-dimensional models using the minimal rank-decomposition condition, and the model reduction is conducted on these two one-dimensional models using time-limited Gramians. The proposed framework works for both one-dimensional and two-dimensional systems. The suggested approach addresses the primary flaw in Gawronski & Juang's problem of reduced-order model instability. Researchers revealed some stability preservation solutions to address this key flaw, which ensure the stability of one-dimensional reduced-order systems; nevertheless, these strategies result in large approximation errors. However, to the best of the authors' knowledge, there is no literature available for the stability preserving time-limited-intervals Gramians based model reduction framework for the two-dimensional discrete-time systems. In comparison to other stability-preserving strategies, the proposed framework provides an a priori error-bound formulation that is easily computable. The simulation results show that the proposed framework performs well compared to other existing stability-preserving methods, demonstrating its usefulness. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DISCRETE-time systems
*APPROXIMATION error
*TWO-dimensional models
Subjects
Details
- Language :
- English
- ISSN :
- 00160032
- Volume :
- 359
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Journal of the Franklin Institute
- Publication Type :
- Periodical
- Accession number :
- 158141703
- Full Text :
- https://doi.org/10.1016/j.jfranklin.2022.06.032