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Title: Iterative Learning Control for High-Speed Rosette Trajectory Tracking

Abstract

We demonstrate high-speed tracking of a selfrepeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace a sum of two sinusoids with different frequencies but identical amplitudes. A feedback controller is combined with an iterative learning controller (ILC) to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies. The ILC eliminates the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two degrees-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate= of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 50% owing to the ILC

Authors:
 [1];  [1]; ORCiD logo [1]
  1. University of Texas at Dallas
Publication Date:
Research Org.:
Univ. of Texas at Dallas, Richardson, TX (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (EE-5A)
OSTI Identifier:
1556919
DOE Contract Number:  
EE0008322
Resource Type:
Conference
Resource Relation:
Conference: 58th IEEE Conference on Decision and Control, Nice, France, December 11th-13th 2019
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; rosette pattern; control; AFM

Citation Formats

Nikooienejad, Nastaran, Maroufi, Mohammad, and Moheimani, S.O. Reza. Iterative Learning Control for High-Speed Rosette Trajectory Tracking. United States: N. p., 2019. Web.
Nikooienejad, Nastaran, Maroufi, Mohammad, & Moheimani, S.O. Reza. Iterative Learning Control for High-Speed Rosette Trajectory Tracking. United States.
Nikooienejad, Nastaran, Maroufi, Mohammad, and Moheimani, S.O. Reza. Wed . "Iterative Learning Control for High-Speed Rosette Trajectory Tracking". United States. https://www.osti.gov/servlets/purl/1556919.
@article{osti_1556919,
title = {Iterative Learning Control for High-Speed Rosette Trajectory Tracking},
author = {Nikooienejad, Nastaran and Maroufi, Mohammad and Moheimani, S.O. Reza},
abstractNote = {We demonstrate high-speed tracking of a selfrepeating non-raster scan AFM pattern known as rosette. To generate this pattern, the lateral axes of the scanner trace a sum of two sinusoids with different frequencies but identical amplitudes. A feedback controller is combined with an iterative learning controller (ILC) to track this repetitive pattern. The feedback controller is designed based on the internal model principle and incorporates the fundamental reference frequencies. The ILC eliminates the repeating deterministic disturbances that appear in the tracking error. To verify the efficacy of the control approach, an experiment is conducted using a two degrees-of-freedom microelectromechanical system nanopositioner to track a rosette pattern sequentially at the rate= of five frames per second. The experimental results show that the root-mean-square value of tracking error has been reduced by more than 50% owing to the ILC},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {12}
}

Conference:
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