Development of a large scanning-range atomic force microscope with adaptive complementary sliding mode controller

Kuan Chia Huang*, Jim Wei Wu, Jyun Jhih Chen, Chih Lieh Chen, Mei Yung Chen, Li Chen Fu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


Atomic force microscopy (AFM) is a powerful technique to provide high resolution, three-dimensional data for measuring topography of samples. However, the scanning range of conventional AFM systems hardly exceeds hundreds of micrometers due to the piezoelectric actuation. In this research, we develop a large scanning-range AFM system with a z-scanner separated from the xy-scanner. The z-scanner actuated by piezoelectric stack provides high speed scanning and the homemade xy-scanner actuated by electromagnetic actuation is capable of 2 mm×2 mm large field positioning with 17 nm rms error. The overall AFM system consists of a commercial piezoelectric positioner, four sets of electromagnetic actuator, a monolithic parallel compliant mechanism, and an eddy current damper. Moreover, a compact disk/digital versatile disk pick-up-head (CD/DVD PUH) is applied to measure the amplitude of the cantilever. Furthermore, we design an adaptive complementary sliding mode controller to deal with the unknown parameters, unmodeled system uncertainties, and the external disturbances. Finally, preliminary experimental results demonstrate the capability of the proposed system.

Original languageEnglish
Article number6426057
Pages (from-to)1685-1690
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Publication statusPublished - 2012
Externally publishedYes
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: 2012 Dec 102012 Dec 13


  • adaptive complementary sliding mode control
  • electromagnetic actuation
  • monolithic parallel compliant mechanism

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization


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