# A Parameter Self-Tuning Decoupling Controller Based on an Improved ADRC for Tension Systems
## 5 Conclusions  
In this paper, a global coupling model of the tension system of the roll-to-roll coating machine is established, the parameter self-tuning decoupling controller based on improved ADRC for the tension system is designed, and simulation experiments are carried out in Simulink. The experiment utilizes GA to carry out the parameter tuning of ADRC, and the experimental results show that GA can complete the parameter tuning of ADRC well and meet the tension control requirements. Experiments in the decoupling performance simulation: using the decoupling controller designed in this paper, the maximum relative error of the other tension unit is 0.012%, using the traditional PID controller, the maximum relative error of the tension unit is 1.5%, the parameter self-tuning decoupling controller based on improved ADRC for tension system has a better decoupling effect; In the anti-interference simulation: the maximum relative error of the decoupling controller designed in this paper is 0.4% for the tension unit under speed interference and 0.016% under tension interference, compared with 17% and 3% for the conventional PID controller, and the parameter self-tuning decoupling controller based on improved ADRC for tension system has a better anti-interference effect; At the same time, the results of other researchers are analyzed and compared with the decoupling controller designed in this paper, and the results show that the tension system decoupling controller designed in this paper is better in the speed interference and tension interference.  
In the future, this paper's decoupled controller will be applied to industrial roll-to-roll coating machines and popularized.  
Conceptualization, G.J. and S.L.; methodology, G.J. and S.L.; software, G.J. and K.W.; validation, G.J., S.L. and H.D.; formal analysis, G.J.; investigation, G.J. and C.W.; resources, S.L.; data curation, G.J. and K.W.; writing--original draft preparation, G.J.; writing--review and editing, G.J. and H.D.; visualization, G.J.; supervision, S.L.; project administration, S.L. and K.W.; funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Program of Shaanxi Province grant number 2023-YBGY-329, Scientific Research Program Funded by Shaanxi Provincial Education Department grant number 22 JY048, Key Research and Development Program of Weinan City grant number ZDYFJH-45 and Lab of Intelligent and Green Flexographic Printing grant number ZBKT202303.  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Controller** & **Perturbation Mode** & **Relative Error** & **Author** & **Reference** \\ \hline FOPID 1 & Tension disturbance & 4.63\% & [PERSON] & [23] \\ REKF-PID 2 & Tension disturbance & 3.74\% & [PERSON] & [24] \\ RD-\(H\infty\) 3 & Speed disturbance & 3.86\% & [PERSON] & [25] \\ \hline \hline \end{tabular} \({}^{\dagger}\) Fractional order PID denoted as FOPID. 2 fuzzy PID controller based on REKF denoted as REKF-PID, Robust Extended Kalman filter is REKF. 3 denoted as RD-\(H\infty\).  
\end{table}
Table 10: Controller performance comparison.  
Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.