• DocumentCode
    2570269
  • Title

    Active vibration control of adaptive truss structure using fuzzy neural network

  • Author

    Zheng, Kai ; Zhang, Yuquan ; Yang, Yiyong ; Yan, Shaoze ; Dou, Lihua ; Chen, Jie

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Beijing Inst. of Technol., Beijing
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    4872
  • Lastpage
    4875
  • Abstract
    This paper presents design, implementation and experimental results of active vibration control of adaptive truss structure using fuzzy neural method. An adaptive truss structure with self-learning active vibration control system is developed. A fuzzy neural network (INN) controller with adaptive membership functions is presented. The experimental setup of a two-bay truss structure with active members is constructed, and the INN controller is applied to vibration suppression of the truss. The controller first senses the output of the accelerometer as an error to activate the adaptation of the weights of the controller, and then a control command signal is calculated based on the INN inference mechanism to drive the active members. Experimental results demonstrate that the active INN controller can effective reduce the truss vibration.
  • Keywords
    adaptive control; fuzzy control; fuzzy neural nets; neurocontrollers; self-adjusting systems; structural engineering; supports; vibration control; adaptive membership function; adaptive truss structure; fuzzy neural network controller; self-learning active vibration control system; Adaptive control; Fuzzy control; Fuzzy neural networks; Programmable control; Vibration control; Adaptive truss structure; Fuzzy neural network(FNN); Vibration control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4598254
  • Filename
    4598254