Stability Optimization of Lower-Limb Exoskeleton Robots Based on Fuzzy Sliding Mode Control

Stability Optimization of Lower-Limb Exoskeleton Robots Based on Fuzzy Sliding Mode Control | 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 Stability Optimization of Lower-Limb Exoskeleton Robots Based on Fuzzy Sliding Mode Control Liang Xuan, Ruizhe Huang, Xiaoyuan Guo, Tengfei Jia, Yufei Xu, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9142832/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With the growing application of lower-limb exoskeleton robots in medical rehabilitation and human movement assistance, achieving high-precision trajectory tracking while rejecting external disturbances has become a key issue. Existing control methods often struggle with unmodeled human dynamics and model uncertainties. While sliding mode control (SMC) offers excellent robustness against these challenges, it typically suffers from the chattering phenomenon. Therefore, this paper focuses on the optimization of robust trajectory tracking for lower-limb exoskeleton robots using fuzzy sliding mode control (FSMC). A mathematical model of the driving joints is established by using a brushless DC motor, and the transfer function of the motor's angular position is derived. Subsequently, a sliding mode controller is designed, and simulation experiments are conducted using step signals, walking, and leg-lifting trajectory inputs. Finally, fuzzy logic is introduced to dynamically adjust the switching gain of the SMC, effectively mitigating chattering and enhancing the exoskeleton's tracking accuracy under human-robot interaction disturbances. This study provides a reliable control scheme for the practical application of lower-limb exoskeletons by addressing system robustness and trajectory tracking precision. Physical sciences/Engineering Physical sciences/Mathematics and computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-9142832","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":613969582,"identity":"1c88a558-e580-4896-bcf2-2ea3b96debb7","order_by":0,"name":"Liang 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Existing control methods often struggle with unmodeled human dynamics and model uncertainties. While sliding mode control (SMC) offers excellent robustness against these challenges, it typically suffers from the chattering phenomenon. Therefore, this paper focuses on the optimization of robust trajectory tracking for lower-limb exoskeleton robots using fuzzy sliding mode control (FSMC). A mathematical model of the driving joints is established by using a brushless DC motor, and the transfer function of the motor's angular position is derived. Subsequently, a sliding mode controller is designed, and simulation experiments are conducted using step signals, walking, and leg-lifting trajectory inputs. Finally, fuzzy logic is introduced to dynamically adjust the switching gain of the SMC, effectively mitigating chattering and enhancing the exoskeleton's tracking accuracy under human-robot interaction disturbances. This study provides a reliable control scheme for the practical application of lower-limb exoskeletons by addressing system robustness and trajectory tracking precision.\u003c/p\u003e","manuscriptTitle":"Stability Optimization of Lower-Limb Exoskeleton Robots Based on Fuzzy Sliding Mode Control","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 06:57:01","doi":"10.21203/rs.3.rs-9142832/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f937d74-8264-4743-90a4-b77983495f63","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-07T07:15:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T00:35:27+00:00","index":66,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-02T20:50:13+00:00","index":65,"fulltext":""},{"type":"reviewerAgreed","content":"309450990904223411358476221281928877611","date":"2026-04-30T19:20:03+00:00","index":64,"fulltext":""},{"type":"reviewerAgreed","content":"263886953153189410183987496113207219418","date":"2026-04-30T15:10:36+00:00","index":63,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":65331614,"name":"Physical sciences/Engineering"},{"id":65331615,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2026-05-07T07:25:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-30 06:57:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9142832","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9142832","identity":"rs-9142832","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}