Application of Neural-Network-Based Vibration Control to Single-Degree-of-Freedom System Structure with Dynamic Vibration Absorber

DOI

Abstract

Using the neural-network-based vibration control suggested by the authors, the control results differ for each learning rate that is to be considered in this paper. A single-degree-of-freedom (SDOF) system structure with a dynamic vibration absorber (DVA) with its damping ratio controlled using neural network algorithm. In actual situation, it is supposed that the neural network algorithm is operated on real time. In the simulation, the control is carried out at the same sampling time of the seismic waves. An optimum-learning rate of the neural network is estimated comparing to the relation between the maximum absolute value of the relative displacements and learning rates. Ten kinds of seismic waves are used as excitation in the simulations.

Journal

Details 詳細情報について

  • CRID
    1390001205209595904
  • NII Article ID
    130004463473
  • DOI
    10.11345/nctam.51.133
  • ISSN
    13494244
    13480693
  • Text Lang
    en
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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