Dynamics Modeling and Tension Control of Composites Winding System Based on ASMC

Hong, Qi; Shi, Yaoyao; Chen, Zhe

doi:10.1109/access.2020.2997340

Cited by 8 publications

(4 citation statements)

References 48 publications

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“…The observer design is based on dead-zone Lyapunov functions; this is an interesting approach that allows achieving convergence of the observer states to compact sets, despite unknown disturbance terms, while avoiding the use of discontinuous signals. Dead-zone Lyapunov functions have been mainly applied to control design: early global stability studies are presented in [20,25,26], and recent studies in [27][28][29][30][31][32]. Additionally, there are a few applications for stability analysis of open loop systems, for instance [33,34].…”

Section: Observer Design and Stability Analysismentioning

confidence: 99%

Design and Evaluation of a Robust Observer Using Dead-Zone Lyapunov Functions—Application to Reaction Rate Estimation in Bioprocesses

2022

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This paper addresses the design and evaluation of a robust observer for second order bioprocesses considering unknown bounded disturbance terms and uncertainty in the dynamics of the unknown and known states. The observer design and the stability analysis are based on dead-zone Lyapunov functions, and a detailed procedure is provided. The transient response bounds and the convergence region of the unknown observer error are determined in terms of the disturbance bounds, considering persistent but bounded disturbances in the dynamics of both the known and unknown observer errors. This is a significant contribution to closely related observer design studies, in which the transient response bounds are determined, but persistent and bounded disturbances are not considered in the dynamics of the known observer error. Other important contributions are: (i) the procedure for defining the observer parameters is significantly simpler than common observer designs, since a solution to the Ricatti equation, solution to LMI constraints, or the accomplishment of eigenvalue inequality conditions are not required; (ii) discontinuous signals are not used in the observer; and (iii) the effect of the gain sign associated with the unknown state in the dynamics of the known state is explicitly and clearly considered in the observer design and in the convergence study. In addition, the guidelines for selecting the observer parameters are provided. Numerical simulation confirms the stability analysis results: the observer errors converge within a short time, with a low estimation error, if observer-parameters are properly defined.

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Section: Observer Design and Stability Analysismentioning

confidence: 99%

Design and Evaluation of a Robust Observer Using Dead-Zone Lyapunov Functions—Application to Reaction Rate Estimation in Bioprocesses

2022

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“…29 And controlling the fabric tension in the winding process is the focus of current research on the control system of the fabric winding mechanism. [35][36][37] The friction coefficient is usually input into the control system as an attribute parameter. Therefore, by embedding this established compound friction model into the control system, the friction coefficient can be dynamically adjusted more accurately, and the control accuracy of the system can be improved.…”

Section: Characterization Model For Fabric/roller Friction Coefficientmentioning

confidence: 99%

Experimental investigation of friction behaviors of glass-fiber woven fabric

Liu

Zhong

et al. 2022

Textile Research Journal

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Friction between the fabric and tool surface is one of the most significant phenomena in manufacturing and application, and it mainly relates to the decisive contact behavior and the influence of tension and relative velocity. This article first investigates the contact behavior between the fabric and roller surface with a visualization method; then explores the influence of the tension and the relative velocity on the friction behavior of fabric/roller; and, finally, proposes a compound friction model considering the effects of tension and velocity and coupling the contact behavior of warp and weft for the friction behavior of glass-fiber woven fabric/roller. The results of a visualization investigation of the contact behavior reveal that the friction between the fabric and the roller is essentially the comprehensive result of the friction between the warp or weft at many fabric interlacing points and the roller. When the tension increases from 29.4 N to 196 N, the static and dynamic friction coefficients of the three fabric samples increased by 39.94%, 40.14%, 32.2%, 88.47%, 42.53%, and 38.17%, respectively. The effect of the velocity is affected by the fabric structure and tension conditions. According to our statistical results, the proposed model was found to agree well with the experimental results from capstan tests.

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“…Tension observer can be realized in programmable logic controller (PLC) and has a hightension observation rate. It has also been studied by many scholars to measure the tension of winding materials for sensorless control [22][23][24]. Hou et al designed a decentralized coordinated control scheme with tension observers for a motor winding system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Yarn-Tension Detection Using Machine Vision Combined with a Tension Observer

Zhou

et al. 2023

Sensors

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Machine vision can prevent additional stress on yarn caused by contact measurement, as well as the risk of hairiness and breakage. However, the speed of the machine vision system is limited by image processing, and the tension detection method based on the axially moving model does not take into account the disturbance on yarn caused by motor vibrations. Thus, an embedded system combining machine vision with a tension observer is proposed. The differential equation for the transverse dynamics of the string is established using Hamilton’s principle and then solved. A field-programmable gate array (FPGA) is used for image data acquisition, and the image processing algorithm is implemented using a multi-core digital signal processor (DSP). To obtain the yarn vibration frequency in the axially moving model, the brightest centreline grey value of the yarn image is put forward as a reference to determine the feature line. The calculated yarn tension value is then combined with the value obtained using the tension observer based on an adaptive weighted data fusion method in a programmable logic controller (PLC). The results show that the accuracy of the combined tension is improved compared with the original two non-contact methods of tension detection at a faster update rate. The system alleviates the problem of inadequate sampling rate using only machine vision methods and can be applied to future real-time control systems.

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Dynamics Modeling and Tension Control of Composites Winding System Based on ASMC

Cited by 8 publications

References 48 publications

Design and Evaluation of a Robust Observer Using Dead-Zone Lyapunov Functions—Application to Reaction Rate Estimation in Bioprocesses

Design and Evaluation of a Robust Observer Using Dead-Zone Lyapunov Functions—Application to Reaction Rate Estimation in Bioprocesses

Experimental investigation of friction behaviors of glass-fiber woven fabric

Dynamic Yarn-Tension Detection Using Machine Vision Combined with a Tension Observer

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