Frequency weighted model order reduction technique and error bounds for discrete time systems
type: Item
instance of: scholarly article
title: Frequency weighted model order reduction technique and error bounds for discrete time systems
zbMATH Open document ID: 1407.93080
DOI: 10.1155/2014/498453
author: Xianqiang Yang
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Model reduction is a process of approximating higher order original models by comparatively lower order models with reasonable accuracy in order to provide ease in design, modeling and simulation for large complex systems. Generally, model reduction techniques approximate the higher order systems for whole frequency range. However, certain applications (like controller reduction) require frequency weighted approximation, which introduce the concept of using frequency weights in model reduction techniques. Limitations of some existing frequency weighted model reduction techniques include lack of stability of reduced order models (for two sided weighting case) and frequency response error bounds. A new frequency weighted technique for balanced model reduction for discrete time systems is proposed. The proposed technique guarantees stable reduced order models even for the case when two sided weightings are present. Efficient technique for frequency weighted Gramians is also proposed. Results are compared with other existing frequency weighted model reduction techniques for discrete time systems. Moreover, the proposed technique yields frequency response error bounds.
Mathematics Subject Classification ID: 93B11
Mathematics Subject Classification ID: 93C55
zbMATH DE Number: 7016593
Wikidata QID: Q59067909
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/498453
OpenAlex ID: W1992787404
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description: scientific article; zbMATH DE number 7016593