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  • Open Access


    A STA Current-Constrained Control for PMSM Speed Regulation System with Function Disturbance Observer

    Bin Zhang, Boqiang Wei*

    Energy Engineering, Vol.119, No.3, pp. 1197-1218, 2022, DOI:10.32604/ee.2022.018411

    Abstract The non-cascade permanent magnet synchronous motor control system has the advantages of simple structure and less adjustable parameters, but the non-cascade structure needs to solve the problem of over-current protection. In this paper, a current constrained control method is used to limit the starting current to a safe range. At the same time, to ensure the robustness and rapidity of the system, a super twist current constraint controller (CCSTA) is generated by combining super twist algorithm (STA) with current constraint control; Considering the diversity of internal and external disturbances, a functional disturbance observer (FDOB) is proposed to compensate the matched… More >

  • Open Access


    An Optimal DF Based Method for Transient Stability Analysis

    Z. A. Zaki1, Emad M. Ahmed1,*, Ziad M. Ali2,3, Imran Khan4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3449-3471, 2022, DOI:10.32604/cmc.2022.020263

    Abstract The effect of energy on the natural environment has become increasingly severe as human consumption of fossil energy has increased. The capacity of the synchronous generators to keep working without losing synchronization when the system is exposed to severe faults such as short circuits is referred to as the power system's transient stability. As the power system's safe and stable operation and mechanism of action become more complicated, higher demands for accurate and rapid power system transient stability analysis are made. Current methods for analyzing transient stability are less accurate because they do not account for misclassification of unstable samples.… More >

  • Open Access


    Design of Network Cascade Structure for Image Super-Resolution

    Jianwei Zhang, Zhenxing Wang, Yuhui Zheng, Guoqing Zhang*

    Journal of New Media, Vol.3, No.1, pp. 29-39, 2021, DOI:10.32604/jnm.2021.018383

    Abstract Image super resolution is an important field of computer research. The current mainstream image super-resolution technology is to use deep learning to mine the deeper features of the image, and then use it for image restoration. However, most of these models mentioned above only trained the images in a specific scale and do not consider the relationships between different scales of images. In order to utilize the information of images at different scales, we design a cascade network structure and cascaded super-resolution convolutional neural networks. This network contains three cascaded FSRCNNs. Due to each sub FSRCNN can process a specific… More >

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