Abstract
Atomic force microscope (AFM) is an important instrument to characterize various nano-scale material properties, such as material viscoelasticity. During the nanometer measurement process of material viscoelasticity, slow measurement velocity and large measurement error are caused by the hysteresis and creep characteristics of piezo actuator which is the core component of AFM. In order to solve the problem, an inversion-based iterative learning control approach was proposed in this paper. By learning the dynamic characteristics of the AFM system in frequency domain, dynamic error in z-axis direction was compensated for to realize the fast and precise positioning of the AFM system. With the proposed approach, the complex modeling process was avoided and the accuracy of the output tracking of expected input was improved. Tribo Indenter produced by DI Inc. was used to measure nanometer viscoelasticity of polydimethylsiloxane (PDMS). The applicability and effectiveness of the proposed approach were verified by the experimental results.
| Original language | American English |
|---|---|
| Pages (from-to) | 154-159 |
| Number of pages | 6 |
| Journal | Nami Jishu yu Jingmi Gongcheng/Nanotechnology and Precision Engineering |
| Volume | 10 |
| Issue number | 2 |
| State | Published - Mar 2012 |
ASJC Scopus subject areas
- Instrumentation
- Mechanical Engineering
- Industrial and Manufacturing Engineering
Keywords
- Atomic force microscope (AFM)
- Dynamic characteristics compensation
- Iterative learning control
- Material viscoelasticity