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.


Optimal Data-Driven Modeling-Free Differential-Inversion-Based Iterative Control: A Wafer Stage Example

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

DSCC2020 - Virtual Conference

Supporting the need among researchers worldwide for additional online and multimedia content, ASME now offers the ASME Conference Video Collection. This platform will collect and provide long-term access to conference presentation videos, encompassing all technology areas within ASME's technical conference and events program. About 30,000-40,000 engineers across all mechanical engineering and related disciplines participate in ASME conferences each year. This includes authors of approximately 6,000 to 8,000 technical papers published by ASME, the majority of whom also submit video presentations for our virtual conferences. The video collection will be available as an add-on to existing product packages or as a separate subscription.