• DocumentCode
    2986602
  • Title

    Novel RS-FNN control policy in hybrid elevator group control system with destination registration

  • Author

    Xu, Yuge ; Luo, Fei

  • Author_Institution
    Coll. of Autom. Sci. & Eng., South China Univ. of Tech., Guangzhou
  • Volume
    1
  • fYear
    2008
  • fDate
    30-31 Aug. 2008
  • Firstpage
    23
  • Lastpage
    28
  • Abstract
    Elevator group control system with destination registration (DR-EGCS) has become hotter in these years. This paper analyzes and obtains the new characteristic attribution in destination registration elevator group control system, firstly builds up a new hybrid elevator group control system with destination registration model is built up based on hybrid system theory and cellular automata. And then aiming at the problem of how to mine the huge complicated, redundant and incomplete original elevator data effectively, one novel elevator group control method combined rough set theory and fuzzy neural network is present. The simulation results show that this proposed hybrid DR-EGCS model is correct and effective. Novel elevator group control method can improve elevator system performance and adapt complicated traffic flow in variable elevator traffic flow conditions. This control method also can be applied to other similar fields.
  • Keywords
    cellular automata; fuzzy control; lifts; neurocontrollers; rough set theory; system theory; DR-EGCS; RS-FNN control policy; cellular automata; destination registration; fuzzy neural network; hybrid elevator group control system; hybrid system theory; rough set theory; variable elevator traffic flow; Automatic control; Communication system traffic control; Control system synthesis; Control systems; Elevators; Fuzzy control; Fuzzy neural networks; Set theory; System performance; Traffic control; Cellular Automata; Elevator Group Control System With Destination Registration; Hybrid System; Rough Set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-2238-8
  • Electronic_ISBN
    978-1-4244-2239-5
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2008.4635744
  • Filename
    4635744