The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach

This study evaluates the performance of passively controlled steel frame building under dynamic loads using time series analysis. A novel application is utilized for the time and frequency domains evaluation to analyze the behavior of controlling systems. In addition, the autoregressive moving avera...

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Main Authors: Mosbeh R. Kaloop, Jong Wan Hu, Yasser Bigdeli
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2017/5482307
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author Mosbeh R. Kaloop
Jong Wan Hu
Yasser Bigdeli
author_facet Mosbeh R. Kaloop
Jong Wan Hu
Yasser Bigdeli
author_sort Mosbeh R. Kaloop
collection DOAJ
description This study evaluates the performance of passively controlled steel frame building under dynamic loads using time series analysis. A novel application is utilized for the time and frequency domains evaluation to analyze the behavior of controlling systems. In addition, the autoregressive moving average (ARMA) neural networks are employed to identify the performance of the controller system. Three passive vibration control devices are utilized in this study, namely, tuned mass damper (TMD), tuned liquid damper (TLD), and tuned liquid column damper (TLCD). The results show that the TMD control system is a more reliable controller than TLD and TLCD systems in terms of vibration mitigation. The probabilistic evaluation and identification model showed that the probability analysis and ARMA neural network model are suitable to evaluate and predict the response of coupled building-controller systems.
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institution Kabale University
issn 1070-9622
1875-9203
language English
publishDate 2017-01-01
publisher Wiley
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series Shock and Vibration
spelling doaj-art-36eb503eebd94db3b3600bf3642f872d2025-08-20T03:55:01ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/54823075482307The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model ApproachMosbeh R. Kaloop0Jong Wan Hu1Yasser Bigdeli2Department of Civil and Environmental Engineering, Incheon National University, Incheon, Republic of KoreaDepartment of Civil and Environmental Engineering, Incheon National University, Incheon, Republic of KoreaDepartment of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, USAThis study evaluates the performance of passively controlled steel frame building under dynamic loads using time series analysis. A novel application is utilized for the time and frequency domains evaluation to analyze the behavior of controlling systems. In addition, the autoregressive moving average (ARMA) neural networks are employed to identify the performance of the controller system. Three passive vibration control devices are utilized in this study, namely, tuned mass damper (TMD), tuned liquid damper (TLD), and tuned liquid column damper (TLCD). The results show that the TMD control system is a more reliable controller than TLD and TLCD systems in terms of vibration mitigation. The probabilistic evaluation and identification model showed that the probability analysis and ARMA neural network model are suitable to evaluate and predict the response of coupled building-controller systems.http://dx.doi.org/10.1155/2017/5482307
spellingShingle Mosbeh R. Kaloop
Jong Wan Hu
Yasser Bigdeli
The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
Shock and Vibration
title The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
title_full The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
title_fullStr The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
title_full_unstemmed The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
title_short The Performance of Structure-Controller Coupled Systems Analysis Using Probabilistic Evaluation and Identification Model Approach
title_sort performance of structure controller coupled systems analysis using probabilistic evaluation and identification model approach
url http://dx.doi.org/10.1155/2017/5482307
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