Full Text:   <126>

Summary:  <18>

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On-line Access: 2022-06-22

Received: 2022-01-03

Revision Accepted: 2022-05-10

Crosschecked: 2022-09-22

Cited: 0

Clicked: 224

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yan-bin SHEN

https://orcid.org/0000-0002-2148-9138

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Journal of Zhejiang University SCIENCE A 2022 Vol.23 No.9 P.721-732

http://doi.org/10.1631/jzus.A2200003


Static control method using gradient–genetic algorithm for grillage adaptive beam string structures based on minimal internal force


Author(s):  Yan-bin SHEN, Hao-song SUN, An-dong LEI, Xiao-yuan YING, Guang YANG, Yao-zhi LUO

Affiliation(s):  College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   benjamin127@163.com

Key Words:  Grillage adaptive beam string structure (GABSS), Gradient‍, –, ‍, genetic algorithm (GGA), Structural control, Adaptive structure, Actuator


Yan-bin SHEN, Hao-song SUN, An-dong LEI, Xiao-yuan YING, Guang YANG, Yao-zhi LUO. Static control method using gradient–genetic algorithm for grillage adaptive beam string structures based on minimal internal force[J]. Journal of Zhejiang University Science A, 2022, 23(9): 721-732.

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author="Yan-bin SHEN, Hao-song SUN, An-dong LEI, Xiao-yuan YING, Guang YANG, Yao-zhi LUO",
journal="Journal of Zhejiang University Science A",
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publisher="Zhejiang University Press & Springer",
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%A Guang YANG
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A1 - Hao-song SUN
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A1 - Guang YANG
A1 - Yao-zhi LUO
J0 - Journal of Zhejiang University Science A
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Abstract: 
The grillage adaptive beam string structure (GABSS) is a new type of smart structure that can self-adjust its deformation and internal forces through a group of active struts (actuators) in response to changes in environmental conditions. In this paper, an internal force control method based on a gradient;genetic algorithm (GGA) is proposed for the static control of a tensioned structure (especially the GABSS). Specifically, an optimization model of the GABSS is established in which the adjustment values of the actuators are set as the control variables, and the internal force of the beam is set as the objective function. The improved algorithm has the advantage of the global optimization ability of the genetic algorithm and the local search ability of the gradient algorithm. Two examples are provided to illustrate the application of the GGA method. The results show that the proposed method is practical for solving the internal force control problem of the GABSS.

采用梯度遗传算法的自适应交叉张弦梁结构最小内力目标静态控制方法

作者:沈雁彬,孙浩淞,雷安东,应萧远,杨光,罗尧治
机构:浙江大学,建筑工程学院,中国杭州,310058
目的:传统控制算法随着自适应结构空间与作动器数量的增加变得低效。本文旨在讨论适用于自适应交叉张弦结构等大空间多变量问题的主动控制算法,并提出自适应双向交叉张弦梁的主动控制模型,探究其在不同环境工况下的承载表现。
创新点:1.以梯度算子改进传统遗传算法,改善其早熟与收敛速度慢的缺陷;2.针对双向交叉张弦梁这一复杂空间结构提出控制方法,并建模验证。
方法:1.在传统遗传算法的选择、交叉和变异算子后加入梯度搜索算子,增强其局部搜索能力与快速收敛能力;2.以作动器作动量作为优化变量,上部梁最小内力工作系数作为目标函数,撑杆与下部索的许用应力作为约束条件,建立自适应双向张弦梁结构的静态主动控制方法;3.通过2×2与3×3的两个算例进行建模控制,以结构内力与位移评价其三种工况下的控制效率,验证所提方法的可行性和有效性。
结论:1.梯度遗传算法具有良好的局部搜索能力和全局优化能力,并且收敛速度快;2.相对传统静态结构,在文中的三种设计工况下,自适应交叉张弦梁结构的承载能力显著提高;3.对于张弦梁结构,风荷载有可能使拉索松弛,造成不利影响,而自适应张弦梁可以使拉索保持受拉状态,并使所有部件协同工作以达到更好的性能。

关键词:交叉张弦梁结构;梯度遗传算法;结构控制;自适应结构;作动器

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