Development of stability-preserving time-limited model reduction framework for 2-D and 1-D models with error bound
Muhammad Imran1
Syeda Hira Ambreen2
Syed Nooh Hamdani2
Muhammad Ejaz Naveed1
Maria Siddiqui2
1.Department of Electrical Engineering,Military College of Signals,(MCS),National University of Sciences and Technology(NUST),Islamabad 43000,Pakistan2.Department of Electrical Engineering, Sir Syed (Center ForAdvanced Studies) Institute of Technology (SSCASE),Islamabad 43000, Pakistan3.College of Science and Humanities, Rumah MajmaahUniversity, Rumah, Kingdom of Saudi Arabia
摘要：Due to their complex structure, 2-D models are challenging to work with;additionally, simulation, analysis, design, and control get increasingly difficult as the order of the model grows. Moreover, in particular time intervals, Gawronski and Juang's time-limited model reduction schemes produce an unstable reduced-order model for the 2-D and 1-D models. Researchers revealed some stability preservation solutions to address this key flaw which ensure the stability of 1-D 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-interval Gramian-based model reduction framework for the 2-D discrete-time systems. In this article, 2-D models are decomposed into two separate sub-models (i.e., two cascaded 1-D models) using the condition of minimal rank-decomposition. Model reduction procedures are conducted on these obtained two 1-D sub-models using limited-time Gramian. The suggested methodology works for both 2-D and 1-D models. Moreover, the suggested methodology gives the stability of the reduced model as well as a priori error-bound expressions for the 2-D and 1-D models. Numerical results and comparisons between existing and suggested methodologies are provided to demonstrate the effectiveness of the suggested methodology.
机标关键词：frameworkdevelopmentstabilitymodelsboundwitherrorpreserving
论文发表日期：2022-08-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：11( 371-381 )
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