Abstract
This article presents a data-driven algorithm that combines the advantages of iterative feedforward tuning and disturbance rejection control to satisfy the precision requirements and ensure extrapolation capability of wafer scanning. The proposed algorithm differs from pre-existing algorithms in terms of its low requirement of system model, high extrapolation capability for non repetitive trajectory tracking tasks, and high tracking precision. The feedforward controller is tuned based on instrumental variables. It utilizes tracking errors from past iterations to eliminate reference-induced errors without requiring a system model. Meanwhile, the system inverse is approximated during iterative process, and then a disturbance rejection control based on iterative tuning is constructed to compensate for disturbance-induced errors. The proposed algorithm is applied to a wafer stage. The experimental results validate the effectiveness and superiority of the proposed algorithm.
Highlights
Gene sequencing is an important scientific technology
The following requirements are imposed on the controller: 1) high tracking precision; 2) strong resistance to disturbance; 3) high extrapolation capability for non repetitive trajectory tracking tasks
(3) Using iterative feedforward tuning (IFFT) to calculate θ ∗ such that the data-based approximation of the system inverse can compensate for the reference-induced error and using Cff to construct a disturbance observer to compensate for the disturbance-induced error, the algorithm becomes data-driven without requiring a system model
Summary
Gene sequencing is an important scientific technology. In the production steps of the next-generation gene sequencing platform, a two-dimensional spot-array is attached to a patterned wafer substrate, and each spot contains a DNA nanoball, which is an amplified DNA cluster. The following requirements are imposed on the controller: 1) high tracking precision; 2) strong resistance to disturbance; 3) high extrapolation capability for non repetitive trajectory tracking tasks. To combine the high control precision of ILC with the extrapolation capability of model-based feedforward control and remove the requirement of system models, many approaches have been investigated. A new data-driven iterativetuning-based compound control strategy that combines both feedforward control and disturbance rejection control is proposed to improve the motion performance of the wafer stage. The main contributions of this study are as follows: 1) A data-driven algorithm that combines feedforward control and disturbance rejection control is proposed, thereby satisfying control precision and extrapolation capability simultaneously without requiring a system model or sensitivity function.
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