Adaptive Robust Backstepping Control for Quadcopter UAV Based on Integral Sliding Mode Surface

Adaptive Robust Backstepping Control for Quadcopter UAV Based on Integral Sliding Mode Surface | 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 Adaptive Robust Backstepping Control for Quadcopter UAV Based on Integral Sliding Mode Surface Yipeng Mao, Chuang Deng, Dong Qing, Weiwei Lv, Yangfan Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9132501/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 May, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract This paper proposes an Integral Sliding Mode-based Adaptive Robust Back-stepping Control (ISM-ARBC) scheme to improve the trajectory tracking and hovering performance of a quadrotor UAV under large-scale time-varying disturbances. It also considers the impact of variations in the payload mass of the UAV, such as in tasks such as power line maintenance or rescue operations. The proposed scheme effectively mitigates the influence of disturbances on the flight process when the upper bound of the time-varying disturbance is unknown, and estimates the potentially uncertain parameters of the system in real time. Using Lyapunov stability theory, it was proven that the designed controller ensured the asymptotic convergence of the tracking error to zero. Furthermore, this paper integrates adaptive control with the concept of integral sliding mode, combining their respective technical characteristics in a complementary manner. The proposed adaptive law, incorporating a σ-modification term, effectively suppresses the chattering inherent in sliding mode control, ensuring system stability. The integration of the sliding mode surface further accelerates the error convergence to zero. The simulation results validate the performance of the proposed control scheme in various scenarios, including continuous weak disturbances, changes in payload mass, and sudden large-scale time-varying disturbances. The results demonstrate that the proposed control scheme has strong robust stabilization 1 and wide applicability, outperforming the traditional adaptive robust control methods. Physical sciences/Engineering Physical sciences/Mathematics and computing Quadrotor UAV Integral sliding mode surface Adaptive robust control Backstepping method Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 May, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 30 Mar, 2026 Reviews received at journal 29 Mar, 2026 Reviews received at journal 26 Mar, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers agreed at journal 25 Mar, 2026 Reviewers invited by journal 25 Mar, 2026 Editor invited by journal 19 Mar, 2026 Editor assigned by journal 17 Mar, 2026 Submission checks completed at journal 17 Mar, 2026 First submitted to journal 15 Mar, 2026 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-9132501","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":612150417,"identity":"722891d9-447b-4e72-baf2-1e6d80f62829","order_by":0,"name":"Yipeng Mao","email":"","orcid":"","institution":"State Grid Sichuan Electric Power Company","correspondingAuthor":false,"prefix":"","firstName":"Yipeng","middleName":"","lastName":"Mao","suffix":""},{"id":612150418,"identity":"f19467f0-982a-402a-9fdc-8385774a0cfd","order_by":1,"name":"Chuang Deng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYBAC/hlg6g8QMzY++ACk2NgJaJG4AaaOATFzsyFIPxszAS0GEWDqMBCzt0nzgNgEtUj3GH4u+HVYzpx/YYO0za9t8nzMDIwfPubg0SJzxlh6Zt9hY8sZDxuMc/tuG7YxMzBLztyGR4tEjoE0b8/hxA03DjYk5/bcZgRqYWPmxa/F+DdQSz1Iy2HLntv2hLVE5JhJ8/w4nGBwvrGxmeHH7USCWiRupJVZ8zYcM9xwg7GZsbfhdnIbM2MzXr/wz0jefJvnzx95g/PHn//48ee27fz25oMfPuLRAgaMbSD7EqAMBsYGAupBAJRe+A9AGaNgFIyCUTAK0AAAzHFZw0u0VyAAAAAASUVORK5CYII=","orcid":"","institution":"State Grid Sichuan Electric Power Company","correspondingAuthor":true,"prefix":"","firstName":"Chuang","middleName":"","lastName":"Deng","suffix":""},{"id":612150419,"identity":"af6aba3a-3f90-4cc7-b501-ea7061d435a7","order_by":2,"name":"Dong Qing","email":"","orcid":"","institution":"State Grid Sichuan Electric Power Company","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"","lastName":"Qing","suffix":""},{"id":612150420,"identity":"56e3f766-b6d5-4cda-99a2-69ec169c345d","order_by":3,"name":"Weiwei Lv","email":"","orcid":"","institution":"State Grid Sichuan Electric Power Company","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Lv","suffix":""},{"id":612150421,"identity":"c5fb4e57-11b3-4100-ad0b-cb260d2da6bb","order_by":4,"name":"Yangfan Yu","email":"","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yangfan","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2026-03-16 03:23:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9132501/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9132501/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-50515-0","type":"published","date":"2026-05-02T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":108809118,"identity":"9a5ce670-f424-4c59-8cfe-9b096504da8e","added_by":"auto","created_at":"2026-05-08 15:50:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6876359,"visible":true,"origin":"","legend":"","description":"","filename":"AdaptiveRobustBacksteppingControl.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9132501/v1_covered_ae4fcb8b-be82-43f8-ae15-66912f4938f6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Adaptive Robust Backstepping Control for Quadcopter UAV Based on Integral Sliding Mode Surface","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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Quadrotor UAV, Integral sliding mode surface, Adaptive robust control, Backstepping method","lastPublishedDoi":"10.21203/rs.3.rs-9132501/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9132501/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This paper proposes an Integral Sliding Mode-based Adaptive Robust Back-stepping Control (ISM-ARBC) scheme to improve the trajectory tracking and hovering performance of a quadrotor UAV under large-scale time-varying disturbances. It also considers the impact of variations in the payload mass of the UAV, such as in tasks such as power line maintenance or rescue operations. The proposed scheme effectively mitigates the influence of disturbances on the flight process when the upper bound of the time-varying disturbance is unknown, and estimates the potentially uncertain parameters of the system in real time. Using Lyapunov stability theory, it was proven that the designed controller ensured the asymptotic convergence of the tracking error to zero. Furthermore, this paper integrates adaptive control with the concept of integral sliding mode, combining their respective technical characteristics in a complementary manner. The proposed adaptive law, incorporating a σ-modification term, effectively suppresses the chattering inherent in sliding mode control, ensuring system stability. The integration of the sliding mode surface further accelerates the error convergence to zero. 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