• DocumentCode
    1992306
  • Title

    Fuzzy RBF Neural Network Control and New Smith Predictor for Hybrid Networked Control Systems

  • Author

    Du Feng ; Du Wencai ; Zhi, Lei

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Hainan Univ., Haikou
  • Volume
    2
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    595
  • Lastpage
    599
  • Abstract
    Wired and wireless network delays highly degrade the control performance of hybrid networked control systems(HNCS). In order to effectively restrain impact of network delay for the HNCS, a novel approach is proposed that new Smith predictor combined with fuzzy radial basis function neural network (FRBFNN), and comes true delay compensations. Because new Smith predictor does not include network delay model, network delay is no need to be measured, identified or estimated on line. It is applicable to some occasions that network delays are random, time-variant and uncertain, and possibly large compared to one, even tens sampling periods. Based on IEEE 802.15.4 (ZigBee) and CSMA/AMP (CAN bus), and there are some data packet dropouts in the inner and outer closed loops, the results of simulation show validity of the control scheme, and indicate that system has better dynamic performance, robustness, self-adaptability and disturbance rejection ability.
  • Keywords
    control engineering computing; delays; fuzzy control; neurocontrollers; predictive control; radial basis function networks; radio networks; Wired network; delay compensation; fuzzy RBF neural network control; fuzzy radial basis function neural network; hybrid networked control system; smith predictor; wireless network delay; Control systems; Degradation; Delay effects; Delay estimation; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Networked control systems; Neural networks; Wireless networks; Smith predictor; fuzzy radial basis function neural network (FRBFNN); hybrid networked control systems; network delay;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Training, 2008. and 2008 International Workshop on Geoscience and Remote Sensing. ETT and GRS 2008. International Workshop on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3563-0
  • Type

    conf

  • DOI
    10.1109/ETTandGRS.2008.343
  • Filename
    5070436