Finite-Frequency LPV H ∞ Control for Disturbed Wind Turbine

Finite-Frequency LPV H ∞ Control for Disturbed Wind Turbine | 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 Article Finite-Frequency LPV H ∞ Control for Disturbed Wind Turbine Shaoping Wang, Bing Wang, Liu Sha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7677011/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract To enhance the robust stability of wind turbines subject to the uncertainties of wind disturbances, a finite-frequency (FF) linear parameter varying (LPV) H ∞ control strategy for maximum power point tracking (MPPT) is proposed through convex analysis and gain scheduling. Specifically, a disturbed wind turbine model is first linearized and convex decomposed, and the wind turbine polytopic LPV state-space model is modeled with wind speed and wind wheel speed as scheduling parameters. Then, the gain scheduling control (GSC) method is employed to design a robust H ∞ control strategy based on the FF domain for wind turbines under MPPT. Theoretically, by exploiting the generalized Kalman-Yakubovich-Popov lemma and linear matrix inequality (LMI) theories, the FF H ∞ performance is evaluated, based on which controller parametrization is addressed. Finally, numerical simulations demonstrate that the proposed control strategy effectively enables the system to track maximum power while ensuring robust stability in the presence of wind disturbances. Physical sciences/Energy science and technology Physical sciences/Engineering Physical sciences/Mathematics and computing Wind turbine Linear parameter varying Finite-frequency Convex analysis Gain scheduling Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 12 Mar, 2026 Reviews received at journal 06 Mar, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviews received at journal 06 Feb, 2026 Reviewers agreed at journal 05 Feb, 2026 Reviews received at journal 22 Jan, 2026 Reviewers agreed at journal 02 Jan, 2026 Reviewers invited by journal 13 Oct, 2025 Editor invited by journal 26 Sep, 2025 Editor assigned by journal 26 Sep, 2025 Submission checks completed at journal 24 Sep, 2025 First submitted to journal 22 Sep, 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. 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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-7677011","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":533828716,"identity":"0f19d111-e9ea-41c7-8d82-952762cddcbf","order_by":0,"name":"Shaoping 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