Control of roll-to-roll manufacturing based on sensorless tension estimation and disturbance compensation

Huang, Pao Yao; Cheng, Ming; Su, Ke; Kuo, Wei Liang

doi:10.1080/02533839.2020.1856724

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…In recent years, various nonlinear control methods such as sliding mode control [11]- [13], intelligent control [14]- [16], backstepping control (BC) [17]- [19], and disturbance compensator [20] have been applied to improve the control quality for the system. These control methods can only improve performance when the system parameters are clearly known.…”

Section: ❒ Issn: 2302-9285mentioning

confidence: 99%

“…Where Wu is the ideal weight vector of the neural network Wu = [W * u1 , W * u2 , ..., W * um ] T , m is the number of neural in the network; and hu is a Gaussian function vector hu = [h u1 , h u2 , ..., h um ] T . The Gaussian function h ui , (i = 1, 2, ..., m), with inputs w u , w r , is defined as (20):…”

Section: Design a Backstepping Control Incorporating Radial Basis Fun...mentioning

confidence: 99%

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Backstepping control with radial basis function neural network for web transport systems

Ly,

Loc,

Thang

et al. 2023

Bulletin EEI

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Web transport system (WTS) is commonly used in the production and handling of web materials such as paper, fabric, corrugated iron, steel, and printing operations. These materials are easily damaged if the process performance is poor. Therefore, high technology in mechanics and precise control techniques are required in this system. In addition, because of parameter variation, strong nonlinearity, and many external noises, there are many challenges in controlling this process. This paper proposes a backstepping technique-based algorithm to control the web’s tension and velocity. To solve the parameter variation, a radial basis function (RBF) neural network-based adaptation algorithm is developed to approximate the varied components in the control algorithm. The system stability is guaranteed using the Lyapunov stability theorem. Simulations in MATLAB/Simulink have been done and the effectiveness of the proposed control algorithm is verified. Tension and velocity tracking can be obtained with parameter variations.

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Section: ❒ Issn: 2302-9285mentioning

confidence: 99%

Section: Design a Backstepping Control Incorporating Radial Basis Fun...mentioning

confidence: 99%

Backstepping control with radial basis function neural network for web transport systems

Ly,

Loc,

Thang

et al. 2023

Bulletin EEI

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show abstract

“…In the modeling of tension system, many scholars have studied the model by considering the effects of speed, diameter, mechanical structure, temperature and humidity, and then conducted serial coupling according to the relationship between subsystems. Huang [1] used the mass conservation law to describe the dynamic relationship between tension and velocity, and considered the effects of friction and inertia moment. Huang [2] analyzed the time-varying characteristics of roller radius and inertia, and established the mechanical structure and dynamic model of unwinding and rewinding system.…”

Section: Introductionmentioning

confidence: 99%

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

Ding¹,

Liu²,

Zhang³

et al. 2023

jist

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It is difficult to precisely control the substrate tension due to the tension system of roll-to-roll coating machine with strong coupling and time-varying parameters. Therefore, a feedforward improved proportional integral derivative (PID) parameters self-tuning decoupling controller of tension system is proposed in this paper. According to the components and working principle of the coating machine, the nonlinear coupling mechanism model of the global tension system is established, and the model is linearized by using the Taylor series. Based on the linear model, a feedforward improved PID parameters self-tuning decoupling controller is designed for tension system. Through the feedforward control compensates the modeled tension and speed interference, a tracking differentiator (TD) is used to improve the performance of PID, and the online self-tuning of PID parameters can be realized by an Radial Basis Function (RBF) identification network. The simulation results show that the proposed decoupling control strategy of tension system can well suppress the coupling interference between the units, and realize the real-time tuning of PID parameters.

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An infinite-order integral disturbance observer for improved estimation of periodic disturbances in motion control systems

Chang

2023

Journal of the Chinese Institute of Engineers

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Control of roll-to-roll manufacturing based on sensorless tension estimation and disturbance compensation

Cited by 5 publications

References 24 publications

Backstepping control with radial basis function neural network for web transport systems

Backstepping control with radial basis function neural network for web transport systems

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

An infinite-order integral disturbance observer for improved estimation of periodic disturbances in motion control systems

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