Stable Control of Wireless Charging under Coil Vibration Situation by A Transfer Learning-based Fuzzy Neural Network

Stable Control of Wireless Charging under Coil Vibration Situation by A Transfer Learning-based Fuzzy Neural Network | 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 Stable Control of Wireless Charging under Coil Vibration Situation by A Transfer Learning-based Fuzzy Neural Network Yunduo Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8842235/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract In recent years, wireless power transfer (WPT) systems have gained significant attention for their convenience,safety, and environmental advantages over traditional charging methods. However, the instability in received voltage due to coil vibration during wireless charging has posed a substantial challenge to the advancement of this technology. To address this issue, this paper proposes optimizing the controller using transfer learning. The optimized controller is designed to ensure stable charging voltage. Specifically, this paper applies transfer learning to enhance a fuzzy neural network (FNN) controller by transferring knowledge from a source domain to a target domain, thereby significantly improving controller performance. Moreover, to mitigate the challenge of insufficient target domain data in transfer learning, a self-correction method is introduced to augment the target domain dataset. To validate the effectiveness of the transfer learning-optimized controller, both simulation and hardware experiments are conducted and compared with four other mainstream controllers. The efficiency of the FNN controller optimized by transfer learning reach 68%, 64%, and 58% under three different disturbance levels, respectively, outperforming the other controllers. Additionally, the maximum voltage deviation is ±2%, and the voltage amplitude is 2.55V, both of which are superior to those of the comparative controllers. Physical sciences/Energy science and technology Physical sciences/Engineering Physical sciences/Mathematics and computing Wireless charging Stable control Fuzzy Neural Network Transfer Learning Optimization Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Apr, 2026 Reviews received at journal 31 Mar, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviews received at journal 28 Feb, 2026 Reviewers agreed at journal 22 Feb, 2026 Reviewers agreed at journal 17 Feb, 2026 Reviewers agreed at journal 16 Feb, 2026 Reviewers invited by journal 16 Feb, 2026 Editor assigned by journal 16 Feb, 2026 Editor invited by journal 16 Feb, 2026 Submission checks completed at journal 13 Feb, 2026 First submitted to journal 13 Feb, 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8842235","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592979977,"identity":"3bc3595b-4b6a-4cfe-a53b-fa6ab5d19a40","order_by":0,"name":"Yunduo Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3PsWoCQRDG8TkWttrz2pHI2aUeEYJdXmWXA7uIEghbSHJg2C1U0uYxLFOeHGy1xtZS30CxsUgR+4S7S5dif/X84RuAIPiHeLcs6KjxJWFsvZd6Wp+0kMvJux/ItuUZ7b2rT1IUdI6NlrQVt+3DK2sw7CbvrWKDIygF1yrnkNi5rE46RUb4iY/RLHY79dEB9JtVdQLSET1hNGOt4U55DoQPdYmyF8kxMkzcjZVhDRLMgAqDanFNoFkiHPRyj31kPEPpnaj9pWvfjv0v/Zzeb8v16aKnaWKX1ckP4m/nQRAEwa++AWz6R3aLuGLwAAAAAElFTkSuQmCC","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":true,"prefix":"","firstName":"Yunduo","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-02-10 14:40:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8842235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8842235/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103050064,"identity":"6c5e63dd-082b-4735-a8c2-9916af9c6d78","added_by":"auto","created_at":"2026-02-20 07:47:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1402479,"visible":true,"origin":"","legend":"","description":"","filename":"StableControlofWirelessChargingunderCoilVibrationSituationbyATransferLearningbasedFuzzyNeuralNetwork.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8842235/v1_covered_8c253bd3-01f1-4a20-9f8e-152cb25bf3d0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stable Control of Wireless Charging under Coil Vibration Situation by A Transfer Learning-based Fuzzy Neural Network","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Wireless charging, Stable control, Fuzzy Neural Network, Transfer Learning, Optimization","lastPublishedDoi":"10.21203/rs.3.rs-8842235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8842235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In recent years, wireless power transfer (WPT) systems have gained significant attention for their convenience,safety, and environmental advantages over traditional charging methods. However, the instability in received voltage due to coil vibration during wireless charging has posed a substantial challenge to the advancement of this technology. To address this issue, this paper proposes optimizing the controller using transfer learning. The optimized controller is designed to ensure stable charging voltage. Specifically, this paper applies transfer learning to enhance a fuzzy neural network (FNN) controller by transferring knowledge from a source domain to a target domain, thereby significantly improving controller performance. Moreover, to mitigate the challenge of insufficient target domain data in transfer learning, a self-correction method is introduced to augment the target domain dataset. To validate the effectiveness of the transfer learning-optimized controller, both simulation and hardware experiments are conducted and compared with four other mainstream controllers. The efficiency of the FNN controller optimized by transfer learning reach 68%, 64%, and 58% under three different disturbance levels, respectively, outperforming the other controllers. Additionally, the maximum voltage deviation is ±2%, and the voltage amplitude is 2.55V, both of which are superior to those of the comparative controllers.","manuscriptTitle":"Stable Control of Wireless Charging under Coil Vibration Situation by A Transfer Learning-based Fuzzy Neural Network","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 12:45:24","doi":"10.21203/rs.3.rs-8842235/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-03T08:06:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-31T12:48:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315674397842594572969192376618747195372","date":"2026-03-31T11:31:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-28T07:44:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201388330753347587327049989181733282889","date":"2026-02-23T00:57:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58529658269826392229895983487338811539","date":"2026-02-17T21:53:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74233333135049182194004783436126826811","date":"2026-02-16T18:42:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-16T14:09:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-16T14:05:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-16T13:49:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-14T04:48:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-14T04:44:19+00:00","index":"","fulltext":""}],"status":"published","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}}],"origin":"","ownerIdentity":"ce8c64ef-b6e4-4263-9474-f0c0e144a56f","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63096735,"name":"Physical sciences/Energy science and technology"},{"id":63096736,"name":"Physical sciences/Engineering"},{"id":63096737,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2026-05-05T01:54:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 12:45:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8842235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8842235","identity":"rs-8842235","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}