Model Reference Adaptive Fuzzy Control of blood glucose level in patients with type 1 diabetes with input saturation

Model Reference Adaptive Fuzzy Control of blood glucose level in patients with type 1 diabetes with input saturation | 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 Model Reference Adaptive Fuzzy Control of blood glucose level in patients with type 1 diabetes with input saturation Fatemeh Soleimannouri, Mohsen Farshad, Saeed Khorashadizadeh, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7280886/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Mar, 2026 Read the published version in Nonlinear Dynamics → Version 1 posted 13 You are reading this latest preprint version Abstract This study proposes a method that combines adaptive control, model references, and fuzzy logic with input saturation to control blood glucose levels in patients with type 1 diabetes. The proposed approach was applied to the nonlinear Bergman model, which accounts for meal disturbances and parameter uncertainties. In the adaptive fuzzy control of a reference model, a mathematical representation of the ideal system is used as a model reference, with the adaptive controller Trying to conform the real system's performance with this ideal model. Furthermore, this method includes an anti-windup compensator to address the system's nonlinear parameters and the Actuator performance degradation caused by input saturation. Furthermore, the controller design was analyzed to ensure the stability and convergence of the parameter error using the Lyapunov theory. To assess the effectiveness of the proposed method in tracking the desired blood glucose level and to compare it with other methods, simulations were conducted in the Simulink environment of MATLAB. The simulation results demonstrate that the proposed controller effectively reaches the desired value, accurately tracks the output during disturbances and parameter uncertainties, and converges faster than other methods. Adaptive fuzzy control of the model reference Disturbance Anti-windup Compensator Type 1 diabetes Lyapunov theory Bergman nonlinear model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Mar, 2026 Read the published version in Nonlinear Dynamics → Version 1 posted Editorial decision: Revision requested 26 Nov, 2025 Reviews received at journal 24 Nov, 2025 Reviews received at journal 11 Nov, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviewers agreed at journal 09 Nov, 2025 Reviewers agreed at journal 07 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 16 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers invited by journal 14 Aug, 2025 Editor assigned by journal 11 Aug, 2025 Submission checks completed at journal 06 Aug, 2025 First submitted to journal 02 Aug, 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. 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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-7280886","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502908309,"identity":"35a07d73-a7c0-4156-b1f4-a8c13300f4b7","order_by":0,"name":"Fatemeh Soleimannouri","email":"","orcid":"","institution":"University of Birjand","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Soleimannouri","suffix":""},{"id":502908310,"identity":"6ab4056d-09f9-4a8d-9542-fb73c0abc0cc","order_by":1,"name":"Mohsen Farshad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDAC5gMMDIwNDIz9EkBSAswGggR8WtgSIFpmziBZy4YbED5ECz6g28b87OPPHXaym283t32wqLkj28B++AHDwz24tZgdYzOezXsm2XjbnYPNMySOPTNu4EkzYEh4hkfL/QZjZsY25sRtNxKbGSTYDic2MOQA/XIAny3snxl/ttUnbp4B0vIPqIX/DSEtPMYMvG2HEzdIALVIAhkNEgRt4Slm5m07bjwD6BcGyb7Dxm0SzwwOEHDYZqDDqmX7Z7c/Zpb4dli2nz/54cMfeLSgAGZgVDKwATGxGoDR+IFopaNgFIyCUTCSAABSSlh0zFnL0gAAAABJRU5ErkJggg==","orcid":"","institution":"University of Birjand","correspondingAuthor":true,"prefix":"","firstName":"Mohsen","middleName":"","lastName":"Farshad","suffix":""},{"id":502908311,"identity":"6551d422-2eb1-4550-bad9-1a6a43d58e52","order_by":2,"name":"Saeed Khorashadizadeh","email":"","orcid":"","institution":"University of Birjand","correspondingAuthor":false,"prefix":"","firstName":"Saeed","middleName":"","lastName":"Khorashadizadeh","suffix":""},{"id":502908312,"identity":"1d72efac-e929-4400-980e-ae532b926289","order_by":3,"name":"Nasser Mehrshad","email":"","orcid":"","institution":"University of Birjand","correspondingAuthor":false,"prefix":"","firstName":"Nasser","middleName":"","lastName":"Mehrshad","suffix":""}],"badges":[],"createdAt":"2025-08-03 02:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7280886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7280886/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11071-026-12328-8","type":"published","date":"2026-03-25T16:10:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":105755603,"identity":"854a9d38-b5e1-4f00-8371-eab7f6deb9e5","added_by":"auto","created_at":"2026-03-30 16:28:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":897500,"visible":true,"origin":"","legend":"","description":"","filename":"article.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7280886/v1_covered_0bab5eb8-5191-4a14-bfe9-42922aab68f9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Model Reference Adaptive Fuzzy Control of blood glucose level in patients with type 1 diabetes with input saturation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nonlinear-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nody","sideBox":"Learn more about [Nonlinear Dynamics](https://www.springer.com/journal/11071)","snPcode":"11071","submissionUrl":"https://submission.nature.com/new-submission/11071/3","title":"Nonlinear Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Adaptive fuzzy control of the model reference, Disturbance, Anti-windup Compensator, Type 1 diabetes, Lyapunov theory, Bergman nonlinear model","lastPublishedDoi":"10.21203/rs.3.rs-7280886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7280886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study proposes a method that combines adaptive control, model references, and fuzzy logic with input saturation to control blood glucose levels in patients with type 1 diabetes. The proposed approach was applied to the nonlinear Bergman model, which accounts for meal disturbances and parameter uncertainties. In the adaptive fuzzy control of a reference model, a mathematical representation of the ideal system is used as a model reference, with the adaptive controller Trying to conform the real system's performance with this ideal model. Furthermore, this method includes an anti-windup compensator to address the system's nonlinear parameters and the Actuator performance degradation caused by input saturation. Furthermore, the controller design was analyzed to ensure the stability and convergence of the parameter error using the Lyapunov theory. To assess the effectiveness of the proposed method in tracking the desired blood glucose level and to compare it with other methods, simulations were conducted in the Simulink environment of MATLAB. 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