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  • Open Access


    Research on Anti-Fluctuation Control of Winding Tension System Based on Feedforward Compensation

    Yujie Duan1, Jianguo Liang1,*, Jianglin Liu1, Haifeng Gao1, Yinhui Li2, Jinzhu Zhang1, Xinyu Wen3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1239-1261, 2024, DOI:10.32604/cmes.2023.044400

    Abstract In the fiber winding process, strong disturbance, uncertainty, strong coupling, and fiber friction complicate the winding constant tension control. In order to effectively reduce the influence of these problems on the tension output, this paper proposed a tension fluctuation rejection strategy based on feedforward compensation. In addition to the bias harmonic curve of the unknown state, the tension fluctuation also contains the influence of bounded noise. A tension fluctuation observer (TFO) is designed to cancel the uncertain periodic signal, in which the frequency generator is used to estimate the critical parameter information. Then, the fluctuation More >

  • Open Access


    An Improved Time Feedforward Connections Recurrent Neural Networks

    Jin Wang1,2, Yongsong Zou1, Se-Jung Lim3,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2743-2755, 2023, DOI:10.32604/iasc.2023.033869

    Abstract Recurrent Neural Networks (RNNs) have been widely applied to deal with temporal problems, such as flood forecasting and financial data processing. On the one hand, traditional RNNs models amplify the gradient issue due to the strict time serial dependency, making it difficult to realize a long-term memory function. On the other hand, RNNs cells are highly complex, which will significantly increase computational complexity and cause waste of computational resources during model training. In this paper, an improved Time Feedforward Connections Recurrent Neural Networks (TFC-RNNs) model was first proposed to address the gradient issue. A parallel… More >

  • Open Access


    Research on VSG Frequency Characteristics and Energy Storage Device Capacity and Charge-Discharge Characteristics Based on Feedforward Branch

    Baoge Zhang1, Shanyan Ping1,*, Haoliang Shi2, Yi Long1, Boxiang Wu1, Yuemin Jiao1

    Energy Engineering, Vol.119, No.6, pp. 2347-2367, 2022, DOI:10.32604/ee.2022.021693

    Abstract Renewable energy is connected to the grid through the inverter, which in turn reduces the inertia and stability of the power grid itself. The traditional grid-connected inverter does not have the function of voltage regulation and frequency regulation and can therefore no longer adapt to the new development. The virtual synchronous generator (VSG) has the function of voltage regulation and frequency regulation, which has more prominent advantages than traditional inverters. Based on the principle of VSG, the relationship between the frequency characteristics and the energy storage capacity of the feedforward branch-based virtual synchronous machine (FVSG) More >

  • Open Access


    Hybrid Deep Learning-Based Adaptive Multiple Access Schemes Underwater Wireless Networks

    D. Anitha1,*, R. A. Karthika2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2463-2477, 2023, DOI:10.32604/iasc.2023.023361

    Abstract Achieving sound communication systems in Under Water Acoustic (UWA) environment remains challenging for researchers. The communication scheme is complex since these acoustic channels exhibit uneven characteristics such as long propagation delay and irregular Doppler shifts. The development of machine and deep learning algorithms has reduced the burden of achieving reliable and good communication schemes in the underwater acoustic environment. This paper proposes a novel intelligent selection method between the different modulation schemes such as Code Division Multiple Access(CDMA), Time Division Multiple Access(TDMA), and Orthogonal Frequency Division Multiplexing(OFDM) techniques using the hybrid combination of the convolutional More >

  • Open Access


    Enabling Smart Cities with Cognition Based Intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine

    Dildar Hussain1, Muhammad Adnan Khan2,*, Sagheer Abbas3, Rizwan Ali Naqvi4, Muhammad Faheem Mushtaq5, Abdur Rehman3, Afrozah Nadeem2

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 141-156, 2021, DOI:10.32604/cmc.2020.013458

    Abstract The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries, including the transportation sector. The worldwide transport departments face many obstacles following the implementation and integration of different vehicle features. One of these tasks is to ensure that vehicles are autonomous, intelligent and able to grow their repository of information. Machine learning has recently been implemented in wireless networks, as a major artificial intelligence branch, to solve historically challenging problems through a data-driven approach. In this article, we discuss recent progress of applying machine learning into vehicle networks for… More >

  • Open Access


    On the Feedforward Control of Hysteresis for a Piezoelectric Plate

    Ligia Munteanu1, Veturia Chiroiu1

    CMC-Computers, Materials & Continua, Vol.28, No.1, pp. 57-80, 2012, DOI:10.3970/cmc.2012.028.057

    Abstract This paper discusses the modeling and feedforward control of hysteresis in a Cantor-like piezoelectric plate. The generalized play operator is analyzed in connection with the plate equations. Results show that hysteresis can be reduced to less than 40% when applying the feedforward control. The subject of the paper belongs to the field of dynamics, characterization and control at the micro/nanoscale. The choose of the Cantor-like piezoelectric plate is motivated by its special property to generate the subharmonic waves due to the anharmonic coupling between the extended-vibration (phonon) and the localized-mode (fracton) regimes. This behavior is… More >

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