Publication:
Data-driven predictive control of exoskeleton for hand rehabilitation with subspace identification

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dc.contributor.authorAKGÜN, GAZİ
dc.contributor.authorsKaplanoglu E., AKGÜN G.
dc.date.accessioned2022-10-26T07:39:52Z
dc.date.accessioned2026-01-10T20:38:51Z
dc.date.available2022-10-26T07:39:52Z
dc.date.issued2022-10-01
dc.description.abstractThis study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabilitation. DDPC is a model-free approach based on past system data. One of the strengths of DDPC is that constraints of states can be added to the controller while performing the controller design. These features of the control algorithm eliminate an essential problem for rehabilitation robots in terms of easy customization and safe repetitive rehabilitation tasks that can be planned within certain constraints. Experiments were carried out with a designed hand rehabilitation system under repetitive and various therapy tasks. Real-time experiment results demonstrate the feasibility and efficiency of the proposed control approach to rehabilitation systems.
dc.identifier.citationKaplanoglu E., AKGÜN G., "Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification", SENSORS, cilt.22, sa.19, 2022
dc.identifier.doi10.3390/s22197645
dc.identifier.issn1424-8220
dc.identifier.issue19
dc.identifier.urihttps://avesis.marmara.edu.tr/api/publication/53b9a465-526b-4188-bbb4-76ceafc61638/file
dc.identifier.urihttps://hdl.handle.net/11424/282633
dc.identifier.volume22
dc.language.isoeng
dc.relation.ispartofSENSORS
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectSinyal İşleme
dc.subjectKimya
dc.subjectAnalitik Kimya
dc.subjectTemel Bilimler
dc.subjectMühendislik ve Teknoloji
dc.subjectInformation Systems, Communication and Control Engineering
dc.subjectSignal Processing
dc.subjectChemistry
dc.subjectAnalytical Chemistry
dc.subjectNatural Sciences
dc.subjectEngineering and Technology
dc.subjectKİMYA, ANALİTİK
dc.subjectTemel Bilimler (SCI)
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectMühendislik
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectALETLER & GÖSTERİM
dc.subjectCHEMISTRY, ANALYTICAL
dc.subjectCHEMISTRY
dc.subjectNatural Sciences (SCI)
dc.subjectENGINEERING, ELECTRICAL & ELECTRONIC
dc.subjectENGINEERING
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectINSTRUMENTS & INSTRUMENTATION
dc.subjectEnstrümantasyon
dc.subjectGenel Mühendislik
dc.subjectElektrik ve Elektronik Mühendisliği
dc.subjectMühendislik (çeşitli)
dc.subjectKimya (çeşitli)
dc.subjectGenel Kimya
dc.subjectFiltrasyon ve Ayırma
dc.subjectFizik Bilimleri
dc.subjectInstrumentation
dc.subjectGeneral Engineering
dc.subjectElectrical and Electronic Engineering
dc.subjectEngineering (miscellaneous)
dc.subjectChemistry (miscellaneous)
dc.subjectGeneral Chemistry
dc.subjectFiltration and Separation
dc.subjectPhysical Sciences
dc.subjectDDPC
dc.subjecthand rehabilitation
dc.subjectsubspace identification
dc.subjectDESIGN
dc.subjectSYSTEM
dc.titleData-driven predictive control of exoskeleton for hand rehabilitation with subspace identification
dc.typearticle
dspace.entity.typePublication

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