Design Decoupling Controller based on Feedforward and Improved PID for Tension System

Ding, Haodi; Liu, Shanhui; Zhang, Han; Wang, Ziyu; Peng, Ming

doi:10.2352/j.imagingsci.technol.2023.67.2.020411

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…Liu et al proposed a parameter self-tuning and self-anti-turbulence control strategy based on an RBF neural network by integrating feed-forward, RBF, and an ADRC, which improved the accuracy of the tension control [12]. Ding et al proposed a feed-forward improved PID parameter self-tuning and decoupling controller, which realized the steady-state control of tension [13]. Kim et al proposed a perturbed machine model that made it possible to handle both nonlinearities and parameter variations of a machine using simple static and first-order dynamic compensators [14].…”

Section: Introductionmentioning

confidence: 99%

A Parameter Self-Tuning Decoupling Controller Based on an Improved ADRC for Tension Systems

Ju,

Liu,

Wei

et al. 2023

Applied Sciences

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Aiming at the problems of strong coupling and time-varying parameters in the tension systems of roll-to-roll coating machines, this paper outlines the design of a parameter self-tuning decoupling controller based on an improved active disturbance rejection controller (ADRC) for tension systems. First, we established a nonlinear coupled model for a global tension system based on the roll-to-roll coating machine tension constituent unit and working principle. Second, we introduced virtual quantities and actual control quantities; then, we applied an ADRC for decoupling control of the tension system based on a nonlinear coupling model, using a genetic algorithm (GA) to achieve parameters tuning in the ADRC. Finally, both the traditional proportional–integral–differential (PID) controller and the designed controller were simulated to evaluate their anti-interference and decoupling performance. Furthermore, the performances of several controllers were compared to the results obtained by other researchers. The result found that the parameter self-tuning decoupling controller based on an improved ADRC for tension systems exhibited better decoupling control performance and that the controller was able to achieve precise control of tension.

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Section: Introductionmentioning

confidence: 99%

A Parameter Self-Tuning Decoupling Controller Based on an Improved ADRC for Tension Systems

Ju,

Liu,

Wei

et al. 2023

Applied Sciences

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Nonlinear model predictive control method for carbon fiber angle link weaving machine tension based on neural network

Zhu,

Wang

2023

2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA)

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Modeling of Accumulator in Roll-to-Roll Coating Equipment and Tension Control with Nonlinear PID

Ju,

Liu,

Feng

et al. 2024

Polymers

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This paper addresses the issue of the high-precision control of substrate tension in an accumulator during the roll-to-roll coating process. First, a coupling model for tension errors in the substrate within the accumulator is established, along with dynamic models for the input–output rollers, carriage, and the thrust model of the ball screw. Based on these models, a simulation model is built in MATLAB/Simulink to analyze the main causes of substrate tension errors in the accumulator under uncontrolled conditions. Next, to tackle the tension errors caused by carriage displacement, a nonlinear proportional–integral–derivative (PID) controller is proposed, and a control strategy for substrate tension in the accumulator is designed. Finally, based on the established simulation model, experiments are conducted using the proposed nonlinear PID controller and the designed tension control strategy, and their performance is compared with that of a classical PID controller. The simulation results show that both the nonlinear PID controller and the classical PID controller, when combined with the proposed tension error control strategy, can reduce tension errors in the accumulator substrate. However, the nonlinear PID controller is more suitable for controlling substrate tension errors in the accumulator. On the one hand, the nonlinear PID controller has better anti-disturbance capability. In the anti-disturbance experiment, under PID control, the substrate tension error remains stable at around −1.6 N, with tension disturbances of ±0.2 N occurring at approximately 185 s and 135 s. On the other hand, the nonlinear PID controller demonstrates better robustness. In the robustness experiment, under the nonlinear PID controller, the substrate tension error fluctuates within the range of 0 to 0.02 N, showing excellent robustness.

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Design Decoupling Controller based on Feedforward and Improved PID for Tension System

Cited by 3 publications

References 13 publications

A Parameter Self-Tuning Decoupling Controller Based on an Improved ADRC for Tension Systems

A Parameter Self-Tuning Decoupling Controller Based on an Improved ADRC for Tension Systems

Nonlinear model predictive control method for carbon fiber angle link weaving machine tension based on neural network

Modeling of Accumulator in Roll-to-Roll Coating Equipment and Tension Control with Nonlinear PID

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