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  • Open Access

    ARTICLE

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

    Shanhui Liu1,*, Haodi Ding1, Ziyu Wang1, Li’e Ma1, Zheng Li2

    Journal of Renewable Materials, Vol.11, No.4, pp. 1991-2014, 2023, DOI:10.32604/jrm.2022.023659

    Abstract 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… More > Graphic Abstract

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

  • Open Access

    ARTICLE

    Nonlinear Identification and Control of Laser Welding Based on RBF Neural Networks

    Hongfei Wei1,*, Hui Zhao2, Xinlong Shi1, Shuang Liang3

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 51-65, 2022, DOI:10.32604/csse.2022.017739

    Abstract A laser beam is a heat source with a high energy density; this technology has been rapidly developed and applied in the field of welding owing to its potential advantages, and supplements traditional welding techniques. An in-depth analysis of its operating process could establish a good foundation for its application in China. It is widely understood that the welding process is a highly nonlinear and multi-variable coupling process; it comprises a significant number of complex processes with random uncertain factors. Because of their nonlinear mapping and self-learning characteristics, artificial neural networks (ANNs) have certain advantages in comparison to traditional methods… More >

  • Open Access

    ARTICLE

    Recognition of Offline Handwritten Arabic Words Using a Few Structural Features

    Abderrahmane Saidi*, Abdelmouneim Moulay Lakhdar, Mohammed Beladgham

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2875-2889, 2021, DOI:10.32604/cmc.2021.013744

    Abstract Handwriting recognition is one of the most significant problems in pattern recognition, many studies have been proposed to improve this recognition of handwritten text for different languages. Yet, Fewer studies have been done for the Arabic language and the processing of its texts remains a particularly distinctive problem due to the variability of writing styles and the nature of Arabic scripts compared to other scripts. The present paper suggests a feature extraction technique for offline Arabic handwriting recognition. A handwriting recognition system for Arabic words using a few important structural features and based on a Radial Basis Function (RBF) neural… More >

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