[1]吴昊,张洵安.巨子有控结构体系非线性地震响应的半主动控制[J].地震工程与工程振动,2017,01(05):155-161.[doi:10.13197/j.eeev.2017.05.155.wuh.018]
 WU Hao,ZHANG Xunan.Semi-active control of nonlinear seismic response for MSCSS[J].EARTHQUAKE ENGINEERING AND ENGINEERING DYNAMICS,2017,01(05):155-161.[doi:10.13197/j.eeev.2017.05.155.wuh.018]
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巨子有控结构体系非线性地震响应的半主动控制
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《地震工程与工程振动》[ISSN:/CN:]

卷:
01
期数:
2017年05期
页码:
155-161
栏目:
论文
出版日期:
2017-10-01

文章信息/Info

Title:
Semi-active control of nonlinear seismic response for MSCSS
作者:
吴昊1 张洵安2
1. 西安理工大学 土木建筑工程学院, 陕西 西安 710048;
2. 西北工业大学 力学与土木建筑学院, 陕西 西安 710072
Author(s):
WU Hao1 ZHANG Xunan2
1. Faculty of Civil Engineering and Architecture, Xi’an University of Technology, Xi’an 710048, China;
2. School of Mechanics and Civil Engineering & Architecture, Northwestern Polytechnical University, Xi’an 710072, China
关键词:
巨子型有控结构体系磁流变阻尼器模糊神经网络非线性振动控制抗震性能
Keywords:
MSCSSMR damperfuzzy neural networknonlinear vibration controlseismic performance
分类号:
TU311.3;T352
DOI:
10.13197/j.eeev.2017.05.155.wuh.018
摘要:
巨子有控结构体系(MSCSS)是一种具有自控能力的新型结构体系。本研究将磁流变(MR)阻尼器与MSCSS的工作机理相结合,采用模糊神经网络建立MR阻尼器的控制规则,利用遗传算法对模糊神经网络结构进行优化,在考虑构件发生非线性变形的情况下,研究了不同场地地震作用时的MSCSS非线性振动响应控制效果。通过与被动控制工况和以LQR算法为基础的半主动控制工况进行时域、频域范围内的对比研究,结果表明本文设计的模糊神经网络算法可以有效减小MSCSS的地震响应,并且在结构构件进入非线性状态以后仍然保持良好的稳定性,大大提高了结构的抗震性能。
Abstract:
Mega-Sub Controlled Structural System, MSCSS for short, is a new form of the tall building systems with self-control ability. This research combines Magneto-Rheological (MR) Damper with structure tectonic mechanism of MSCSS, and presents the application of MR dampers in nonlinear vibration control of MSCSS subjected to severe earthquake excitation. The semi-active control rules of MR dampers were designed by using fuzzy neural network, and the genetic algorithm was applied to optimize the rules of fuzzy neural network by taking the displacement and acceleration of the top floor as optimizing objective. By contrast with the vibration control effect of MSCSS with passive control and semi-active control based on LQR algorithm in time domain and frequency domain, we can conclude that the MR dampers with fuzzy neural network proposed in this paper can significantly reduce the seismic response of MSCSS, even when the structural element into nonlinear state, fuzzy neural network can still keep good vibration control effect, it greatly improve the seismic performance of MSCSS.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-09-10;改回日期:2016-12-17。
基金项目:陕西省教育厅专项科研计划项目(16JK1547);西安理工大学科技创新计划项目(2014CX017);陕西省自然科学基础研究计划项目(2017JQ5062)
作者简介:吴昊(1984-),男,讲师,主要从事工程结构抗震及其振动控制研究.E-mail:wuhao@xaut.edu.cn
更新日期/Last Update: 2017-10-25