Optimal data-driven modeling-free differential-inversion-based iterative control: A wafer stage example

Zezhou Zhang, Qingze Zou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, an optimal data-driven modeling-free differential-inversion-based iterative control (OMFDIIC) method is proposed for both high performance and robustness in the presence of random disturbances. Achieving high accuracy and fast convergence is challenging as the system dynamics behaviors vary due to the external uncertainties and the system bandwidth is limited. The aim of the proposed method is to compensate for the dynamics effect without modeling process and achieve both high accuracy and robust convergence, by extending the existed modeling-free differential-inversion-based iterative control (MFDIIC) method through a frequency- and iteration- dependent gain. The convergence of the OMFDIIC method is analyzed with random noise/disturbances considered. The developed method is applied to a wafer stage, and shows a significant improvement in the performance.

Original languageEnglish (US)
Title of host publicationIntelligent Transportation/Vehicles; Manufacturing; Mechatronics; Engine/After-Treatment Systems; Soft Actuators/Manipulators; Modeling/Validation; Motion/Vibration Control Applications; Multi-Agent/Networked Systems; Path Planning/Motion Control; Renewable/Smart Energy Systems; Security/Privacy of Cyber-Physical Systems; Sensors/Actuators; Tracking Control Systems; Unmanned Ground/Aerial Vehicles; Vehicle Dynamics, Estimation, Control; Vibration/Control Systems; Vibrations
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791884287
DOIs
StatePublished - 2020
EventASME 2020 Dynamic Systems and Control Conference, DSCC 2020 - Virtual, Online
Duration: Oct 5 2020Oct 7 2020

Publication series

NameASME 2020 Dynamic Systems and Control Conference, DSCC 2020
Volume2

Conference

ConferenceASME 2020 Dynamic Systems and Control Conference, DSCC 2020
CityVirtual, Online
Period10/5/2010/7/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Automotive Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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