Iterative Learning Control for Video-Rate Atomic Force Microscopy
| Autor: | Nastaran Nikooienejad, S. O. Reza Moheimani, Mohammad Maroufi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Adaptive control Computer science Iterative learning control Feed forward Ranging 02 engineering and technology Tracking (particle physics) Frame rate Computer Science Applications 020901 industrial engineering & automation Control and Systems Engineering Control theory Filter (video) Electrical and Electronic Engineering |
| Zdroj: | IEEE/ASME Transactions on Mechatronics. 26:2127-2138 |
| ISSN: | 1941-014X 1083-4435 |
| Popis: | We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller. The iterative learning controller is designed to improve tracking performance of the feedback-controlled scanner by rejecting the repetitive disturbances arising from the system nonlinearities. We investigate the performance of two inversion techniques for constructing the learning filter. We conduct tracking experiments using a two-degree-of-freedom microelectromechanical system (MEMS) nanopositioner at frame rates ranging from 5 to 20 frames per second. The results reveal that the algorithm converges rapidly and the iterative learning controller significantly reduces both the transient and steady-state tracking errors. We acquire and report a series of high-resolution time-lapsed video-rate AFM images with the rosette pattern. |
| Databáze: | OpenAIRE |
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