Disturbance observer-based tracking control for roll-to-roll slot die coating systems under gap and pump rate disturbances

TL;DR

This paper introduces a disturbance observer-based control system for roll-to-roll slot die coating, improving process stability and film quality by mitigating disturbances in key control parameters using data-driven modeling and simulation validation.

Contribution

The paper presents a novel disturbance observer and generalized compensator integrated with output tracking control for roll-to-roll coating systems, validated through a data-driven model and simulation.

Findings

Enhanced disturbance rejection in coating process

Improved accuracy in maintaining coating thickness

Validated effectiveness through simulation results

Abstract

Roll-to-roll slot die coating is a widely used industrial manufacturing technique applied in a diverse range of applications such as the production of lithium-ion batteries, solar cells and optical films. The efficiency of roll-to-roll slot die coating depends on the precise control of various input parameters such as pump rate, substrate velocity and coating gap. However, these inputs are sensitive to disturbances in process conditions, leading to inconsistencies in the various characteristics of the produced film. To address this challenge, a \gls{DO} is utilized for detecting disturbances, which may occur in the same or different channels as the control signal within the system. A generalized compensator is then implemented to mitigate the impact of these disturbances on the output, thereby enhancing uncertainty suppression. Additionally, integrating the disturbance rejection system with an output tracking controller enables the coating system to maintain the desired thickness under varying input conditions and disturbances. The effectiveness of this approach is then validated using a test rig equipped with a camera system, which facilitates the development of a data-driven model of the dynamic process, represented by state-space equations. The simulation results were demonstrated to showcase the effectiveness of the DOBOTC system, which provides a resilient solution for the output tracking issue in a data-driven model with generalized disturbances.