Optimal design, modeling and analysis of a 2-DOF nanopositioning stage with dual-mode: Towards High-Rate AFM scanning

Hui Tang, Yangmin Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)

Abstract

A compliant 2-DOF nanopositioning stage with a novel concept of dual-mode driven is proposed in this paper aiming to improve the scanning performance of the Atomic Force Microscope (AFM). The stage is featured with nanoscale positioning precision, high bandwidth, long scanning range and fully decoupled structure, which can be selected to work in dual working modes. Based upon the matrix method, the discussions in terms of output compliance, input stiffness and dynamics modeling via Lagrange equation have been performed in detail. Moreover, a series of optimal designs have been implemented using Particle Swarm Optimization (PSO) algorithm. The results of the finite-element analysis (FEA) indicate that the first natural frequency is approximated 583 Hz, the amplification ratio in two axes is about 4, thus the maximum scanning range can reach up to around 341 μm × 341 μm without material failure, while the cross-coupling between the two axes is kept within 2%. All the results indicate that the presented mechanism possesses a good performance for high-rate AFM scanning.
Original languageEnglish
Title of host publication2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
Pages658-663
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2012
Externally publishedYes
Event25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012 - Vilamoura, Algarve, Portugal
Duration: 7 Oct 201212 Oct 2012

Conference

Conference25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
Country/TerritoryPortugal
CityVilamoura, Algarve
Period7/10/1212/10/12

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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