Frequency-weighted and frequency interval Gramian framework-based model reduction using singular value decomposition

被引:0
|
作者
Sharma, Vineet [1 ,2 ]
Kumar, Deepak [1 ]
机构
[1] MNNIT Allahabad, EED, Prayagraj 211004, Uttar Pradesh, India
[2] Poornima Coll Engn, EED, Jaipur 302017, Rajasthan, India
关键词
controllability and observability Gramians; reduced-order model; frequency weights; frequency interval; singular value decomposition; BALANCED TRUNCATION; LINEAR-SYSTEMS;
D O I
10.1093/imamci/dnad036
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is observed that the reduced-order models (ROMs) by some existing limited Gramians-based techniques deviate significantly from the high-order model, resulting in a large approximation inaccuracy. Therefore, this paper introduces a novel solution for finite-frequency model reduction using new frequency-weighted Gramians by employing balanced truncation. This work provides a novel structure of fictitious input and output matrices, resulting in the proposed continuous-time system Gramians. The suggested strategy provides stable ROMs even when input and output weightings are incorporated into the system. Furthermore, the proposed approach is extended with the frequency-interval Gramians, ensuring stable ROMs. The proposed simulation outcomes are compared with other well-known frequency-weighted and frequency-interval Gramians-based techniques using numerical examples to demonstrate the efficacy of the suggested strategies.
引用
收藏
页码:57 / 72
页数:16
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