• DocumentCode
    76201
  • Title

    Precision Sinusoidal Local Scan for Large-Range Atomic Force Microscopy With Auxiliary Optical Microscopy

  • Author

    Chih-Lieh Chen ; Jim-Wei Wu ; Yi-Ting Lin ; Li-Chen Fu ; Mei-Yung Chen

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    20
  • Issue
    1
  • fYear
    2015
  • fDate
    Feb. 2015
  • Firstpage
    226
  • Lastpage
    236
  • Abstract
    Atomic force microscopy (AFM) is a powerful measurement instrument which can build 3-D topography image of conductive and nonconductive samples at nanoscale resolution. However, due to the scan method of conventional AFM, the induced mechanical resonance of the scanner and the scan in area of uninterest would strictly limit the scan speed. In this study, we improve these problems with our designed AFM system from three aspects. First, the sinusoidal trajectory is applied to lateral scanning of the AFM rather than the traditional raster trajectory, so the scan rate can be increased without inducing vibration of the lateral scanner. Second, with this promising scan trajectory, the internal model principle-based neural network complementary sliding-mode controller and adaptive complementary sliding-mode controller are designed to achieve high precision scanning and to cope with the system parameter uncertainties and external disturbance. Finally, with the aid of an auxiliary optical microscopy and the scanned information during the scanning process, scan path planning can be adopted to focus the scanning on samples such that the total scan time is further shortened. Extensive experimental results are provided to show the appealing performance of the proposed method.
  • Keywords
    adaptive control; atomic force microscopy; measurement uncertainty; neurocontrollers; optical scanners; surface topography; variable structure systems; 3D topography image; AFM system; adaptive complementary sliding mode controller; atomic force microscopy; auxiliary optical microscopy; internal model principle-based neural network complementary sliding mode controller; mechanical resonance; nanoscale resolution; nonconductive sample; precision sinusoidal local scan method; scan path planning; scanner; scanning process; sinusoidal trajectory; system parameter uncertainty; Atomic force microscopy; Electromagnetics; Force; Optical imaging; Optical microscopy; Trajectory; Adaptive control; atomic force microscopy (AFM); complementary sliding-mode control; internal model principle (IMP); neural network; sinusoidal scan;
  • fLanguage
    English
  • Journal_Title
    Mechatronics, IEEE/ASME Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4435
  • Type

    jour

  • DOI
    10.1109/TMECH.2014.2313351
  • Filename
    6787105