Automation, Control and Intelligent Systems

Volume 4, Issue 6, December 2016

  • Improvement of Echo State Network Generalization by Selective Ensemble Learning Based on BPSO

    Xiaodong Zhang, Xuefeng Yan

    Issue: Volume 4, Issue 6, December 2016
    Pages: 84-88
    Received: 29 November 2016
    Published: 1 December 2016
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    Abstract: The Echo State Network (ESN) is a novel and special type of recurrent neural network that has become increasingly popular in machine learning domains such as time series forecasting, data clustering, and nonlinear system identification. This network is characterized by large randomly constructed recurrent neural networks (RNN) called “reservoir”, i... Show More
  • Barcode Recognizable System Implementing Based on AM5728

    Xicai Li, Junsheng Shi, Xiaoqiao Huang, Yonghang Tai, Chongde Zi, Huan Yang, Xingyu Yang, Zhiwei Deng, Feiyan Li

    Issue: Volume 4, Issue 6, December 2016
    Pages: 89-94
    Received: 29 November 2016
    Published: 1 December 2016
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    Abstract: To refine the implementation of industrial camera requirements in terms of barcode identification, speeding the barcode image acquisition and processing challenges, as well as the defect of low accuracy. We proposed a barcode recognition framework based on AM5728 embedded system, which employed industrial CCD to scan the barcode image, moreover, in... Show More
  • Control of Flexible Joint Robot Using Integral Sliding Mode and Backstepping

    Sungha Kwon, Abner Asignacion, Seungkyu Park

    Issue: Volume 4, Issue 6, December 2016
    Pages: 95-100
    Received: 6 December 2016
    Accepted: 20 December 2016
    Published: 16 January 2017
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    Abstract: The control of flexible joint robot is getting more attentions because its applications are more frequently used for robot systems in these days. This paper proposes a robust impedance controller for flexible joint robots by using integral sliding mode control and backstepping control. The sliding mode control decouple disturbances completely but r... Show More