Neuro-control of seismically excited steel structure through sensitivity evaluation scheme SCIE SCOPUS

Cited 26 time in WEB OF SCIENCE Cited 28 time in Scopus
Title
Neuro-control of seismically excited steel structure through sensitivity evaluation scheme
Author(s)
Kim, DH; Lee, IW
Publication Year
2001-09
Abstract
The neuro-controller training algorithm based on cost function is applied to a multi-degree-of-freedom system; and a sensitivity evaluation algorithm replacing the emulator neural network is proposed. In conventional methods, the emulator neural network is used to evaluate the sensitivity of structural response to the control signal. To use the emulator, it should be trained to predict the dynamic response of the structure. Much of the time is usually spent on training of the emulator. In the proposed algorithm, however, it takes only one sampling time to obtain the sensitivity. Therefore, training time for the emulator is eliminated. As a result, only one neural network is used for the neuro-control system. In the numerical example, the three-storey building structure with linear and non-linear stiffness is controlled by the trained neural network. The actuator dynamics and control time delay are considered in the simulation. Numerical examples show that the proposed control algorithm is valid in structural control. Copyright (C) 2001 John Wiley & Sons, Ltd.
ISSN
0098-8847
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/5863
DOI
10.1002/eqe.67
Bibliographic Citation
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, v.30, no.9, pp.1361 - 1377, 2001
Publisher
JOHN WILEY & SONS LTD
Subject
ACTIVE CONTROL; NETWORKS; SYSTEMS
Keywords
neural network; control; vibration; sensitivity; emulator; training
Type
Article
Language
English
Document Type
Article
Publisher
JOHN WILEY & SONS LTD
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