frequency weighted model reduction technique with error bounds Santa Paula California

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frequency weighted model reduction technique with error bounds Santa Paula, California

Numerically robust algorithms based on square root and balancing free techniques are proposed for frequency weighted balanced truncation techniques. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.AbstractModel reduction This may lead to a large change in some eigenvalues and may not affect other eigenvalues. Equations (18) and (19) can be expressed as

JavaScript is disabled on your browser. degree from University of Victoria, Canada in 1989, all in electrical engineering.He worked as a Project Engineer in the Indian Space Research Organisation from 1983 to 1985. Let ๎€be contragredient matrixobtained as๎€๐‘‡๎€˜๐‘’๐‘›๎€=๎€โˆ’1๎€—๐‘’๐‘›๎€โˆ’๐‘‡ =diag ๎€ž๎€Ÿ1,๎€Ÿ2,๎€Ÿ3,...,๎€Ÿ๐‘›๎€ , (๎€ˆ)where ๎€Ÿ๐‘—โ‰ฅ๎€Ÿ๐‘—+1, ๎€ข = 1,2,3,...,๎€ฃโˆ’1and ๎€Ÿ๐‘™>๎€Ÿ๐‘™+1.Bytransforming and then partitioning the original system, wehave๎€ค

The balancing procedure involves computation of transformation matrix from controllability and observability Gramians. A new frequency weighted technique for balanced model reduction for discrete time systems is proposed. See all โ€บ7 CitationsSee all โ€บ55 ReferencesShare Facebook Twitter Google+ LinkedIn Reddit Download Full-text PDF A Frequency Weighted Model Order Reduction Technique and Error BoundsArticle (PDF Available)โ€‚inโ€‚Automatica 50(12)ย ยทย December 2014โ€‚withโ€‚46 ReadsDOI: 10.1016/j.automatica.2014.10.062 Varga and Anderson's [38] tend to minimize the distance between Enns and Campbell et al.'s techniques Gramians by eliminating negative eigenvalues.In this work, a technique is developed for frequency weighted balanced

Several numerical examples illustrate the effectiveness of the proposed approach. Please note that Internet Explorer version 8.x will not be supported as of January 1, 2016. Campbell et al.’s Technique [37]Campbell et al.’s [37] (a discrete time version of [28]) guarantees the positive semidefiniteness of symmetric matrices and to ensure stability. He is currently working towards the Ph.D.

Click the View full text link to bypass dynamically loaded article content. Please update your favourites accordingly Search Results Previous Searches Refine your search Brief view Table view Full view Sort by: Title Author Year Record 1 of 1 1 Frequency-weighted model Please try the request again. Results are compared with other existing frequency weighted model reduction techniques for discrete time systems.

Both continuous and discrete time systems are considered, in one and two-dimensions. However, certain applications (like controllerreduction) require frequency weighted approximation, which introduce the concept of using frequency weights in model reductiontechniques. The Cholesky factors and satisfy and [4].(4) Proposed Technique. Most model reduction algorithms tend to minimizethe reduction error over the whole frequency range; howeverthere are certain situations (like controller reduction [๎€„๎€‡]),wherein the approximation error is more critical over acertain band

ScienceDirect ยฎ is a registered trademark of Elsevier B.V.RELX Group Recommended articles No articles found. Campbell et al.โ€™s [๎€†๎€]techniqueisdiscretetimecounterpart of Wang et al.โ€™s [๎€„๎€ˆ] technique, which not onlyprovides stability for two sided case but also gives easilycomputable error bounds. Your cache administrator is webmaster. Varga and Anderson [29] technique yields proper model for strictly proper systems also.

A new frequency weighted technique for balancedmodel reduction for discrete time systems is proposed. ๎€‰e proposed technique guarantees stable reduced order models even forthe case when two sided weightings are present. Enns Technique [25]Let be contragredient matrix obtained as where and . Unfortunately, most of these techniques yield large frequency response error [30] as compared to Enns technique. It is desirable that reduced ordermodel preserves the fundamental properties of originalsystem like stability, passivity, and so forth.

US & Canada: +1 800 678 4333 Worldwide: +1 732 981 0060 Contact & Support About IEEE Xplore Contact Us Help Terms of Use Nondiscrimination Policy Sitemap Privacy & Opting Out C., 1981], [Liu, Y, et al., 1989] and the partial fraction expansion technique [Sreeram, V, et al., 1995]. The method is illustrated using numerical examples and the results are compared with other frequency weighted model reduction techniques.KeywordsModel reduction; Gramians; Frequency weighted; Balanced truncation; Error boundsโ˜†The material in this paper or its licensors or contributors.

degree at the same University.His research interest include control systems, model/controller reduction and signal processing.Abdul Ghafoor received the B.S. Let the new controllability and observability Gramians, respectively, be calculated by solving the following Lyapunov equations: which are used to obtain contragredient matrix as where and , and . However, [35] incorporates free parameters to reduce the approximation error.Most frequently, frequency weighted model reduction problem is treated in continuous time; however, there are few papers (like [36–38]) which deal with Use of this web site signifies your agreement to the terms and conditions.