MIMO Model Order Reduction by Padé-Markov Least Squares and Frequency Data Fitting

MIMO Model Order Reduction by Padé-Markov Least Squares and Frequency Data Fitting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article MIMO Model Order Reduction by Padé-Markov Least Squares and Frequency Data Fitting Marcelo A. Oliveira, Roberto Ades, Paulo C. Pellanda This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5234507/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Sep, 2025 Read the published version in Journal of Control, Automation and Electrical Systems → Version 1 posted 9 You are reading this latest preprint version Abstract This paper presents a new analytical method for model order reduction of dynamic systems, appli- cable to both SISO and MIMO models. The method is structured into two stages: the first stage computes a common characteristic polynomial using Pad´e coeffcients and Markov parameters; the second stage estimates the gain and zeros by optimally fitting the frequency response data using a quadratic norm criterion. The resulting reduced-order model is obtained by solving systems of linear equations, avoiding iterative procedures and numerical optimization algorithms. The method extends existing approaches by ensuring a unified denominator across all MIMO channels and provides an exact analytical solution for the optimal numerator coeffcients. The convexity of the cost function guaran- tees global optimality. The effectiveness and versatility of the proposed approach are demonstrated through three case studies, including systems with unstable and non-minimum phase characteristics. The results show that the method yields competitive accuracy compared to the available techniques in the frequency domain. Model order reduction Padé approximation Markov parameters Frequency response fitting MIMO systems Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 Sep, 2025 Read the published version in Journal of Control, Automation and Electrical Systems → Version 1 posted Editorial decision: Revision requested 22 May, 2025 Reviews received at journal 05 May, 2025 Reviews received at journal 01 May, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers invited by journal 23 Apr, 2025 Submission checks completed at journal 21 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5234507","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447692210,"identity":"9fe6264b-27e4-4c4c-843f-9d2e953f6a76","order_by":0,"name":"Marcelo A. 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