000084386 001__ 84386
000084386 005__ 20230126102836.0
000084386 0247_ $$2doi$$a10.3390/mi10090597
000084386 0248_ $$2sideral$$a114011
000084386 037__ $$aART-2019-114011
000084386 041__ $$aeng
000084386 100__ $$0(orcid)0000-0003-3823-7903$$aDíaz Pérez, Lucía$$uUniversidad de Zaragoza
000084386 245__ $$aTrajectory definition with high relative accuracy (HRA) by parametric representation of curves in nano-positioning systems
000084386 260__ $$c2019
000084386 5060_ $$aAccess copy available to the general public$$fUnrestricted
000084386 5203_ $$aNanotechnology applications demand high accuracy positioning systems. Therefore, in order to achieve sub-micrometer accuracy, positioning uncertainty contributions must be minimized by implementing precision positioning control strategies. The positioning control system accuracy must be analyzed and optimized, especially when the system is required to follow a predefined trajectory. In this line of research, this work studies the contribution of the trajectory definition errors to the final positioning uncertainty of a large-range 2D nanopositioning stage. The curve trajectory is defined by curve fitting using two methods: traditional CAD/CAM systems and novel algorithms for accurate curve fitting. This novel method has an interest in computer-aided geometric design and approximation theory, and allows high relative accuracy (HRA) in the computation of the representations of parametric curves while minimizing the numerical errors. It is verified that the HRA method offers better positioning accuracy than commonly used CAD/CAM methods when defining a trajectory by curve fitting: When fitting a curve by interpolation with the HRA method, fewer data points are required to achieve the precision requirements. Similarly, when fitting a curve by a least-squares approximation, for the same set of given data points, the HRA method is capable of obtaining an accurate approximation curve with fewer control points.
000084386 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/E41-17R$$9info:eu-repo/grantAgreement/ES/DGA-FEDER/2014-2020$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-69403-C3-1-R$$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-096321-B-I00
000084386 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000084386 590__ $$a2.523$$b2019
000084386 591__ $$aINSTRUMENTS & INSTRUMENTATION$$b23 / 64 = 0.359$$c2019$$dQ2$$eT2
000084386 591__ $$aNANOSCIENCE & NANOTECHNOLOGY$$b65 / 103 = 0.631$$c2019$$dQ3$$eT2
000084386 592__ $$a0.531$$b2019
000084386 593__ $$aControl and Systems Engineering$$c2019$$dQ2
000084386 593__ $$aMechanical Engineering$$c2019$$dQ2
000084386 593__ $$aElectrical and Electronic Engineering$$c2019$$dQ2
000084386 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000084386 700__ $$0(orcid)0000-0001-9130-0794$$aRubio Serrano, Beatriz$$uUniversidad de Zaragoza
000084386 700__ $$0(orcid)0000-0003-4839-0610$$aAlbajez García, José A.$$uUniversidad de Zaragoza
000084386 700__ $$0(orcid)0000-0001-7152-4117$$aYagüe Fabra, José A.Y$$uUniversidad de Zaragoza
000084386 700__ $$0(orcid)0000-0002-1101-6230$$aMainar Maza, Esmeralda$$uUniversidad de Zaragoza
000084386 700__ $$0(orcid)0000-0002-3069-2736$$aTorralba Gracia, Marta
000084386 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDpto. Matemática Aplicada$$cÁrea Matemática Aplicada
000084386 7102_ $$15002$$2515$$aUniversidad de Zaragoza$$bDpto. Ingeniería Diseño Fabri.$$cÁrea Ing. Procesos Fabricación
000084386 773__ $$g10, 9 (2019), 597 [19 pp.]$$pMicromachines (Basel)$$tMICROMACHINES$$x2072-666X
000084386 8564_ $$s3430345$$uhttps://zaguan.unizar.es/record/84386/files/texto_completo.pdf$$yVersión publicada
000084386 8564_ $$s109368$$uhttps://zaguan.unizar.es/record/84386/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000084386 909CO $$ooai:zaguan.unizar.es:84386$$particulos$$pdriver
000084386 951__ $$a2023-01-26-09:53:51
000084386 980__ $$aARTICLE