Trajectory definition with high relative accuracy (HRA) by parametric representation of curves in nano-positioning systems

Díaz Pérez, Lucía (Universidad de Zaragoza) ; Rubio Serrano, Beatriz (Universidad de Zaragoza) ; Albajez García, José A. (Universidad de Zaragoza) ; Yagüe Fabra, José A.Y (Universidad de Zaragoza) ; Mainar Maza, Esmeralda (Universidad de Zaragoza) ; Torralba Gracia, Marta

Resumen: 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.

Idioma: Inglés

DOI: 10.3390/mi10090597

Año: 2019

Publicado en: MICROMACHINES 10, 9 (2019), 597 [19 pp.]
ISSN: 2072-666X

Factor impacto JCR: 2.523 (2019)

Categ. JCR: INSTRUMENTS & INSTRUMENTATION rank: 23 / 64 = 0.359 (2019) - Q2 - T2
Categ. JCR: NANOSCIENCE & NANOTECHNOLOGY rank: 65 / 103 = 0.631 (2019) - Q3 - T2

Factor impacto SCIMAGO: 0.531 - Control and Systems Engineering (Q2) - Mechanical Engineering (Q2) - Electrical and Electronic Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FEDER/E41-17R
Financiación: info:eu-repo/grantAgreement/ES/DGA-FEDER/2014-2020
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2015-69403-C3-1-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-096321-B-I00

Tipo y forma: Article (Published version)

Área (Departamento): Área Matemática Aplicada (Dpto. Matemática Aplicada)
Área (Departamento): Área Ing. Procesos Fabricación (Dpto. Ingeniería Diseño Fabri.)