Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation

Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation | 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 Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation Boyu Dang, Haiyan Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3924063/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract This study presents a novel event-triggered finite-time stochastic control method for a robot manipulator. The random moment of inertia of the manipulator system is expressed by building a stochastic dynamic model, and the parameter variation disturbance is estimated by using a stochastic configuration neural network. An event-triggered controller with uncertain disturbance rejection is proposed, which not only realizes the stochastic finite-time stability of the tracking error system, but also guarantees the safety of motion velocity, and robustly improves the tracking accuracy of the robot manipulator. Compared with the existing works, the obvious feature of the proposed method is that it can simultaneously solve the random disturbance and uncertain parameter disturbance of the manipulator system, save communication resources, and ensure that the manipulator system can reach a steady state in finite time. We also discuss the effectiveness of the proposed stochastic tracking control method. Simulation and comparative analysis results further show that the controller can be updated less frequently while guaranteeing robust tracking performance of the robot manipulator. Robot manipulator Event-triggered finite-time control Stochastic tracking control Uncertain disturbance estimation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Feb, 2024 Reviews received at journal 23 Feb, 2024 Reviews received at journal 17 Feb, 2024 Reviewers agreed at journal 14 Feb, 2024 Reviewers agreed at journal 12 Feb, 2024 Reviewers invited by journal 08 Feb, 2024 Editor assigned by journal 07 Feb, 2024 Submission checks completed at journal 06 Feb, 2024 First submitted to journal 03 Feb, 2024 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-3924063","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271650344,"identity":"0b0a26b5-6a18-404a-9ec4-0430ee68bbad","order_by":0,"name":"Boyu Dang","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Boyu","middleName":"","lastName":"Dang","suffix":""},{"id":271650345,"identity":"e04d0957-8e84-4aa9-bfbf-c2556c8d6ca2","order_by":1,"name":"Haiyan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3PPWrDMBTAcQmBsrxEa0R7CIEhHxDSq0gYPJkuhS4dqiBwFh9AuUjXyhicJSRrS5aWXsDePHSom9Ihi5yxUP2nJ3g/JCEUCv3BRgQQkt3ACF7Xsl0AY9pP6C/ha1OhJk+uuXU9BMHPIHZVgi0tF0LLHjIYFvV7trxFL+nkA+AAAjlcN6nvYaN4rLL4Dtt0GsHsCFOiCd88ef8iOkKUGafiCuAIc+0oGfpJ1KrsUWUnQvcgnOwlk+6WUuVQJdxSdxmZyf1W2YEpRZPHwG1hvH9hbBe9tvcP6rnEqzfZLm8YM0XdeMgpTM+Pumf/u88LdkKhUOj/9gUfrE6W0pHrPgAAAABJRU5ErkJggg==","orcid":"","institution":"Northeastern University","correspondingAuthor":true,"prefix":"","firstName":"Haiyan","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-02-03 13:29:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3924063/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3924063/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50873924,"identity":"ce3d3302-a1ae-408e-a15b-4a7bcea1e568","added_by":"auto","created_at":"2024-02-08 18:12:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1407662,"visible":true,"origin":"","legend":"","description":"","filename":"snarticle20240203.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3924063/v1_covered_085a3327-9bf1-4543-85a2-2b7691edd71e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation","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":"Robot manipulator, Event-triggered finite-time control, Stochastic tracking control, Uncertain disturbance estimation","lastPublishedDoi":"10.21203/rs.3.rs-3924063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3924063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study presents a novel event-triggered finite-time stochastic control method for a robot manipulator. 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