An Improve Nonlinear Robust Control Approach for Robotic Manipulators with PSO-based Global Optimization Strategy

An Improve Nonlinear Robust Control Approach for Robotic Manipulators with PSO-based Global Optimization Strategy | 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 An Improve Nonlinear Robust Control Approach for Robotic Manipulators with PSO-based Global Optimization Strategy Peihao Yue, Bowen Xu, Min Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4192866/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract During the trajectory tracking process of robotic manipulators, many factors including complex strong nonlinear dynamics, unknown uncertainties and external disturbances, greatly increase the difficulty of control effect. Aiming for this issue, a nonlinear active disturbance rejection controller (NADRC) is proposed for robotic manipulators. In this controller, an extended state observer is introduced on basis of the dynamic model, to observe the extend state of model uncertainties and external disturbances. Then, in combination with the nonlinear feedback control structure, the robust trajectory tracking of robotic manipulators is achieved. Furthermore. In order to optimize the key parameters of the controller, an improved particle swarm optimization algorithm (IPSO) was designed using chaos theory, which improves the tracking accuracy of the proposed NDRC strategy effectively. Finally, the effectiveness of the proposed control strategy was verified through simulation experiments. Robotic manipulator Nonlinear dynamics Active disturbance rejection controller Nonlinear control Particle swarm optimization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 21 Jun, 2024 Reviewers agreed at journal 15 May, 2024 Reviews received at journal 09 May, 2024 Reviews received at journal 08 May, 2024 Reviewers agreed at journal 29 Apr, 2024 Reviewers agreed at journal 29 Apr, 2024 Reviewers invited by journal 29 Apr, 2024 Editor assigned by journal 23 Apr, 2024 Editor invited by journal 13 Apr, 2024 Submission checks completed at journal 12 Apr, 2024 First submitted to journal 30 Mar, 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. 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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-4192866","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":290723893,"identity":"add4549b-7f6e-4c04-8f21-30a216d1f9ca","order_by":0,"name":"Peihao Yue","email":"","orcid":"","institution":"Hunan University","correspondingAuthor":false,"prefix":"","firstName":"Peihao","middleName":"","lastName":"Yue","suffix":""},{"id":290723894,"identity":"5d0b2a44-708a-45b2-b330-e93215551374","order_by":1,"name":"Bowen Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYDACCSD+YCDBzM/MfPgB0VoYZ1RYsEu2s6UZEK2FmedMBb/BeR4FCaJ0GNzuMWDgbZOQNj7Mw2DAUGMTTVCL5JwzBgySbRLGZod5DzxgOJaW20BIC79E7gYGwzaJZLPDfAkGjA2HCWthA2lJbJOo39zMYyBBlBawLQfOSDAbMBOrRXLO+Q+MDRUSzBKHgYGcQIxfDG63JTD/Mahj5u8/fPjBhxobwlqAgP0HnJlAhPJRMApGwSgYBUQAAGKFOP9VZSjkAAAAAElFTkSuQmCC","orcid":"","institution":"Hunan Academy of Forestry Sciences","correspondingAuthor":true,"prefix":"","firstName":"Bowen","middleName":"","lastName":"Xu","suffix":""},{"id":290723895,"identity":"c19ba0e2-eb52-4843-bded-6b8deb72cd53","order_by":2,"name":"Min Zhang","email":"","orcid":"","institution":"Hunan Academy of Forestry Sciences","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-03-30 15:45:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4192866/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4192866/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-72156-x","type":"published","date":"2024-09-13T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64619252,"identity":"2b1c91a5-0294-4ef7-8eaf-fd8f17c43de2","added_by":"auto","created_at":"2024-09-16 16:13:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":917916,"visible":true,"origin":"","legend":"","description":"","filename":"FINALArticleManuscript20240410.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4192866/v1_covered_621ab2cd-4563-4de1-b631-0bdd1611340e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Improve Nonlinear Robust Control Approach for Robotic Manipulators with PSO-based Global Optimization Strategy","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":"Robotic manipulator, Nonlinear dynamics, Active disturbance rejection controller, Nonlinear control, Particle swarm optimization","lastPublishedDoi":"10.21203/rs.3.rs-4192866/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4192866/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"During the trajectory tracking process of robotic manipulators, many factors including complex strong nonlinear dynamics, unknown uncertainties and external disturbances, greatly increase the difficulty of control effect. 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