ANN based methodology for active control of buildings for seismic excitation for different seismic zones of India

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• 作者：A. Goel^&lowast ; ; ^{abgoel92@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; P. Kamatchi^&lowast ; &lowast ; ; ^{kamat@serc.res.in" class="auth_mail" title="E-mail the corresponding author} ; P. Jayabalan^&lowast ; &lowast ; &lowast ; ; ^{pjeya@nitt.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：ANN ; Active Control ; Seismic Zones ; Stochastic GM generation ; Earthquake ; Building
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：1
• 页码：95-99
• 全文大小：596 K

文摘

In the last two decades, many studies are reported in literature for determining the control force for the active control systems for damage mitigation of buildings due to earthquake. However, no study has been reported for prediction of control force considering the seismic zones in India. In the present study, spectrum compatible time histories are generated for the seismic zones IV and V as per Indian standard IS 1893(Part 1):2002 design spectrum. Time history analysis are carried out with spectrum compatible time histories for shear type buildings modelled as multi-degree of freedom system (MDOF) with a computer program developed in MATLAB by modal superposition using Newmark-beta method. Control forces are obtained by adopting algorithm proposed in literature and input and output patterns are generated for development of Artificial Neural Network (ANN) models in Stuttgart Neural Network Simulator (SNNS). In the present study the methodology is demonstrated with five storey building by developing 24 ANN models consisting of two ANN architectures viz., NET1 and NET2 for each seismic zone and three soil types. From the validation of results from ANN models it is observed that the maximum difference in percentage response reduction of peak displacement is less than 10% when it is compared with the target value of percentage response reduction.