Active control of plane frames by compatible neural network

Controlling the behavior of frame building is very common these days. This goal is achieved by changing the structural behaviors through applying forces to the frames. Recently, extensive studies have been carried out in the field of structural control related to the earthquakes. All studies conduct...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Mohammad Rezaiee-Pajand, Mahdi Payandeh suni
Formato:	article
Lenguaje:	FA
Publicado:	Iranian Society of Structrual Engineering (ISSE) 2019
Materias:	structural control neural network variable neurons genetic algorithm predicting earthquake acceleration closed circle earthquake Bridge engineering TG1-470 Building construction TH1-9745
Acceso en línea:	https://doaj.org/article/60f278459ac64a01a38b0a265ba19038
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:60f278459ac64a01a38b0a265ba19038
record_format	dspace
spelling	oai:doaj.org-article:60f278459ac64a01a38b0a265ba190382021-11-08T15:52:41ZActive control of plane frames by compatible neural network2476-39772538-261610.22065/jsce.2018.95322.1287https://doaj.org/article/60f278459ac64a01a38b0a265ba190382019-08-01T00:00:00Zhttps://www.jsce.ir/article_60364_13b0b974c3bd6f40f8942faa1d1d4284.pdfhttps://doaj.org/toc/2476-3977https://doaj.org/toc/2538-2616Controlling the behavior of frame building is very common these days. This goal is achieved by changing the structural behaviors through applying forces to the frames. Recently, extensive studies have been carried out in the field of structural control related to the earthquakes. All studies conducted in this area can be divided into two groups. The first category is devoted to the control devices. Since accuracy and sensitivity of required equipment play an important role, some industries are trying to build better and more robust instruments. The key subject of the second group of researchers is developing new control algorithms. These approaches need some innovations. The purpose of this study is to minimize the structural response against earthquake utilizing two actuators. The purpose of this study is to minimize the structural response against earthquake utilizing two actuators. The relationship between the control forces of the actuators was so arranged that the first mode force becomes zero. In order to minimize the structural responses, the genetic algorithm was used. The controlling system, which is exploited in this paper, is a closed circle. In addition, the neural network was employed to predict the earth acceleration. The authors selected a kind of the neural network to have compatibility with earthquake acceleration variation. To achieve this, the number of the neurons in layers should be varied. The comprehensive experimental numerical results for a variety of earthquakes and structures indicated that the suggested method is very effective. However, the present study drawback is in decreasing the responses of tall frames.Mohammad Rezaiee-PajandMahdi Payandeh suniIranian Society of Structrual Engineering (ISSE)articlestructural controlneural networkvariable neuronsgenetic algorithmpredicting earthquake accelerationclosed circleearthquakeBridge engineeringTG1-470Building constructionTH1-9745FAJournal of Structural and Construction Engineering, Vol 6, Iss شماره ویژه 2, Pp 191-210 (2019)
institution	DOAJ
collection	DOAJ
language	FA
topic	structural control neural network variable neurons genetic algorithm predicting earthquake acceleration closed circle earthquake Bridge engineering TG1-470 Building construction TH1-9745
spellingShingle	structural control neural network variable neurons genetic algorithm predicting earthquake acceleration closed circle earthquake Bridge engineering TG1-470 Building construction TH1-9745 Mohammad Rezaiee-Pajand Mahdi Payandeh suni Active control of plane frames by compatible neural network
description	Controlling the behavior of frame building is very common these days. This goal is achieved by changing the structural behaviors through applying forces to the frames. Recently, extensive studies have been carried out in the field of structural control related to the earthquakes. All studies conducted in this area can be divided into two groups. The first category is devoted to the control devices. Since accuracy and sensitivity of required equipment play an important role, some industries are trying to build better and more robust instruments. The key subject of the second group of researchers is developing new control algorithms. These approaches need some innovations. The purpose of this study is to minimize the structural response against earthquake utilizing two actuators. The purpose of this study is to minimize the structural response against earthquake utilizing two actuators. The relationship between the control forces of the actuators was so arranged that the first mode force becomes zero. In order to minimize the structural responses, the genetic algorithm was used. The controlling system, which is exploited in this paper, is a closed circle. In addition, the neural network was employed to predict the earth acceleration. The authors selected a kind of the neural network to have compatibility with earthquake acceleration variation. To achieve this, the number of the neurons in layers should be varied. The comprehensive experimental numerical results for a variety of earthquakes and structures indicated that the suggested method is very effective. However, the present study drawback is in decreasing the responses of tall frames.
format	article
author	Mohammad Rezaiee-Pajand Mahdi Payandeh suni
author_facet	Mohammad Rezaiee-Pajand Mahdi Payandeh suni
author_sort	Mohammad Rezaiee-Pajand
title	Active control of plane frames by compatible neural network
title_short	Active control of plane frames by compatible neural network
title_full	Active control of plane frames by compatible neural network
title_fullStr	Active control of plane frames by compatible neural network
title_full_unstemmed	Active control of plane frames by compatible neural network
title_sort	active control of plane frames by compatible neural network
publisher	Iranian Society of Structrual Engineering (ISSE)
publishDate	2019
url	https://doaj.org/article/60f278459ac64a01a38b0a265ba19038
work_keys_str_mv	AT mohammadrezaieepajand activecontrolofplaneframesbycompatibleneuralnetwork AT mahdipayandehsuni activecontrolofplaneframesbycompatibleneuralnetwork
_version_	1718441666236383232

Active control of plane frames by compatible neural network

Ejemplares similares