Neural-network sliding mode control of nonlinear systems via a fuzzy integral switching function

Neural-network sliding mode control of nonlinear systems via a fuzzy integral switching function | 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 Neural-network sliding mode control of nonlinear systems via a fuzzy integral switching function Xiaofei Fan, Tao Li, Yufeng Tian, Guoying Miao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3742264/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Dec, 2024 Read the published version in Nonlinear Dynamics → Version 1 posted 4 You are reading this latest preprint version Abstract A neural-network fuzzy sliding mode control (NNFSMC) problem for nonlinear systems via a fuzzy integral switching function (FISF) is investigated in this paper. Different from the existing results on sliding mode control (SMC), a novel FISF is presented to fully utilize the fuzzy membership functions, which is consisted by the four parts. The fuzzy membership functions and state variables are together used to design the first two terms of FISF. Meanwhile, an integral term on a derivative of fuzzy membership function is considered to design the last term. Combining with the designed FISF, a Gaussian radial basic neural network is used to design a NNFSMC law, which can effectively reduce the amplitude of the high-frequency chattering. Furthermore, a fuzzy Lyapunov method and a switching idea are applied to analyze the asymptotical stability of the developed systems, which can reduce the conservatism of asymptotic stability criteria. In the end, the availability and advantages of the proposed theoretical results can be verified via two simulations. Nonlinear systems fuzzy systems fuzzy switching function sliding mode control neural network Full Text Cite Share Download PDF Status: Published Journal Publication published 31 Dec, 2024 Read the published version in Nonlinear Dynamics → Version 1 posted Reviewers agreed at journal 22 Dec, 2023 Reviewers invited by journal 22 Dec, 2023 Editor assigned by journal 12 Dec, 2023 First submitted to journal 12 Dec, 2023 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. 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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-3742264","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":262705370,"identity":"d4fff4ce-fa52-4f84-ab8a-7671896c2cb6","order_by":0,"name":"Xiaofei Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIie3Qv0oDMRzA8d8RyC0pv/UX9CFSBItweK+SUrjpcHQSCRxkEru2L+KcEuhmfQCXe4AOd4t0UUw9B5emNzrkO+QP5ENIAFKpf1huwqABENjPvhCIJk6EG4g0A6ku5cqNIHAkw+wLZfQZkr9uqX0oCHPgbW/fhAKXdX0dIeJuofS2ItlAPl3bdzFjhsn1y2lSQj1tNfePygO/mARyYxxnkwgRuFdOf3kqj+TT7kTYniEUbplbT4oFklk3huyv1Py5Igq3yKfdQsjVpom+RWB9LQ8f4ceWjtPh/rZEbDZdHyF/wu53kZlR51OpVCp1um8OK0jlHmmaIQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-1412-9679","institution":"Nanjing University of Information Science and Technology","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiaofei","middleName":"","lastName":"Fan","suffix":""},{"id":262705371,"identity":"4d631b22-5521-46e3-a345-de1357c30b0e","order_by":1,"name":"Tao Li","email":"","orcid":"","institution":"Nanjing University of Information Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Li","suffix":""},{"id":262705372,"identity":"d3b7a1e0-f710-49ca-b6d5-e2782c74f10a","order_by":2,"name":"Yufeng Tian","email":"","orcid":"","institution":"Chongqing University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yufeng","middleName":"","lastName":"Tian","suffix":""},{"id":262705373,"identity":"14bb2505-5dd8-4aae-b670-ac46fb685e32","order_by":3,"name":"Guoying Miao","email":"","orcid":"","institution":"Nanjing University of Information Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guoying","middleName":"","lastName":"Miao","suffix":""}],"badges":[],"createdAt":"2023-12-12 06:57:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3742264/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3742264/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11071-024-10783-9","type":"published","date":"2024-12-31T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":73093415,"identity":"cfeb6c15-de74-4371-b671-a8ccd049194d","added_by":"auto","created_at":"2025-01-06 16:17:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1149362,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3742264/v1_covered_42a5bdd4-dbfb-4568-98dd-a5b3bd405715.pdf"}],"financialInterests":"","formattedTitle":"Neural-network sliding mode control of nonlinear systems via a fuzzy integral switching function","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":true,"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":"Nonlinear systems, fuzzy systems, fuzzy switching function, sliding mode control, neural network","lastPublishedDoi":"10.21203/rs.3.rs-3742264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3742264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"A neural-network fuzzy sliding mode control (NNFSMC) problem for nonlinear systems via a fuzzy integral switching function (FISF) is investigated in this paper. 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