Application of Neural-Network-Based Vibration Control to Single-Degree-of-Freedom System Structure with Dynamic Vibration Absorber
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- HIRATSUKA Kiyotoshi
- Shingu Laboratory, Nihon University
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- SHINGU Kiyoshi
- College of Science and Technology, Nihon University
Description
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
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- Theoretical and Applied Mechanics Japan
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Theoretical and Applied Mechanics Japan 51 (0), 133-140, 2002
National Committee for IUTAM
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Details 詳細情報について
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- CRID
- 1390001205209595904
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- NII Article ID
- 130004463473
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- ISSN
- 13494244
- 13480693
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- Text Lang
- en
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed