Design Decoupling Controller for Rewinding System of the Gravure Printing Machines

Wang, Ziyu; Liu, Shanhui; He, Kunjin; Shi, Wenliang; Chen, Siwei

doi:10.1109/itoec49072.2020.9141756

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…Meng et al [22] suggested a solution combining the seeker optimization method and ADRC regulator for tension control. Liu et al [23,24] suggested decoupled control based on ADRC regulator to address the issue of tension control for unwinding and rewinding mechanisms of the gravure printer. Zhang et al [25] designed an ADRC regulator by considering parameter uncertainty and various disturbances in a stainless-steel strip production line.…”

Section: Introductionmentioning

confidence: 99%

An RBF neural network–based parameter tuning for an ADRC regulator of electrode wire feed mechanism: arc welding applications

Babes,

Boutaghane,

Reddaf

et al. 2024

Weld World

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The electrode wire feeding mechanism (EWFM) is a closed-loop system that is commonly utilized in power controlled arc welding machines to achieve better performance for different electrode wire diameters. This study presents parameters self-tuning method based on RBF neural network for active disturbance rejection controller (ADRC) of a welding EWFM, and establishes a real-time testing system based on the dSPACE platform. First, an ADRC control strategy is developed to enhance the tracking performance and robustness of a welding EWFM in a multi-source disturbance environment. Second, an RBF-based parameters tuning method is provided to correctly determine and adjust the gains of the suggested ADRC regulator. Finally, to con rm the considered strategy, the real-time tests are conducted.The ndings demonstrate that the suggested ADRC regulator with RBF-based gains tuning algorithm has a considerable disturbance rejection capability, small overshoot, fast response, and high precision which can improve the stability and quality of the arc welding process.

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Section: Introductionmentioning

confidence: 99%

An RBF neural network–based parameter tuning for an ADRC regulator of electrode wire feed mechanism: arc welding applications

Babes,

Boutaghane,

Reddaf

et al. 2024

Weld World

View full text Add to dashboard Cite

show abstract

“…Meng proposed the method combined with seeker optimization algorithm and ADRC for tension control [14]. Liu et al [15,16] respectively proposed a decoupling controller based on ADRC to solve the problem of tension control for unwinding and rewinding tension system of gravure printing machines. Zhang et al [17] considered the parameter uncertainty and the multi-disturbance of the stainless-steel strip processing line and designed an ADRC controller.…”

Section: Introductionmentioning

confidence: 99%

An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network

Liu¹,

Ding²,

Wang³

et al. 2023

Journal of Renewable Materials

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High precision control of substrate tension is the premise and guarantee for producing high-quality products in roll-to-roll precision coating machine. However, the complex relationships in tension system make the problems of decoupling control difficult to be solved, which has limited the improvement of tension control accuracy for the coating machine. Therefore, an ADRC parameters self-tuning decoupling strategy based on RBF neural network is proposed to improve the control accuracy of tension system in this paper. Firstly, a global coupling nonlinear model of the tension system is established according to the composition of the coating machine, and the global coupling model is linearized based on the first-order Taylor formula. Secondly, according to the linear model of the tension system, a parameters self-tuning decoupling algorithm of the tension system is proposed by integrating feedforward control, ADRC and RBF. Finally, the simulation results show that the proposed tension control strategy has good decoupling control performance and effectively improves the tension control accuracy for the coating machine.

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Design Tension Controller for the Rewinding System of Roll-to-roll Precision Coating Machine

Wang¹,

Liu²,

Jiao³

et al. 2021

2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)

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Design Decoupling Controller for Rewinding System of the Gravure Printing Machines

Cited by 6 publications

References 12 publications

An RBF neural network–based parameter tuning for an ADRC regulator of electrode wire feed mechanism: arc welding applications

An RBF neural network–based parameter tuning for an ADRC regulator of electrode wire feed mechanism: arc welding applications

An ADRC Parameters Self-Tuning Control Strategy of Tension System Based on RBF Neural Network

Design Tension Controller for the Rewinding System of Roll-to-roll Precision Coating Machine

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