84386 20230126102836.0 doi 10.3390/mi10090597 sideral 114011 ART-2019-114011 eng Díaz Pérez, Lucía Universidad de Zaragoza (orcid)0000-0003-3823-7903 Trajectory definition with high relative accuracy (HRA) by parametric representation of curves in nano-positioning systems 2019 Access copy available to the general public Unrestricted Nanotechnology 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. info:eu-repo/grantAgreement/ES/DGA-FEDER/E41-17R info:eu-repo/grantAgreement/ES/DGA-FEDER/2014-2020 info:eu-repo/grantAgreement/ES/MINECO/DPI2015-69403-C3-1-R info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-096321-B-I00 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.523 2019 INSTRUMENTS & INSTRUMENTATION 23 / 64 = 0.359 2019 Q2 T2 NANOSCIENCE & NANOTECHNOLOGY 65 / 103 = 0.631 2019 Q3 T2 0.531 2019 Control and Systems Engineering 2019 Q2 Mechanical Engineering 2019 Q2 Electrical and Electronic Engineering 2019 Q2 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Rubio Serrano, Beatriz Universidad de Zaragoza (orcid)0000-0001-9130-0794 Albajez García, José A. Universidad de Zaragoza (orcid)0000-0003-4839-0610 Yagüe Fabra, José A.Y Universidad de Zaragoza (orcid)0000-0001-7152-4117 Mainar Maza, Esmeralda Universidad de Zaragoza (orcid)0000-0002-1101-6230 Torralba Gracia, Marta (orcid)0000-0002-3069-2736 2005 595 Universidad de Zaragoza Dpto. Matemática Aplicada Área Matemática Aplicada 5002 515 Universidad de Zaragoza Dpto. Ingeniería Diseño Fabri. Área Ing. Procesos Fabricación 10, 9 (2019), 597 [19 pp.] Micromachines (Basel) MICROMACHINES 2072-666X 3430345 http://zaguan.unizar.es/record/84386/files/texto_completo.pdf Versión publicada 109368 http://zaguan.unizar.es/record/84386/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:84386 articulos driver 2023-01-26-09:53:51 ARTICLE