CLC number:
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2022-09-22
Cited: 0
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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.
@article{title="Static control method using gradient–genetic algorithm for grillage adaptive beam string structures based on minimal internal force",
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",
volume="23",
number="9",
pages="721-732",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2200003"
}
%0 Journal Article
%T Static control method using gradient–genetic algorithm for grillage adaptive beam string structures based on minimal internal force
%A Yan-bin SHEN
%A Hao-song SUN
%A An-dong LEI
%A Xiao-yuan YING
%A Guang YANG
%A Yao-zhi LUO
%J Journal of Zhejiang University SCIENCE A
%V 23
%N 9
%P 721-732
%@ 1673-565X
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2200003
TY - JOUR
T1 - Static control method using gradient–genetic algorithm for grillage adaptive beam string structures based on minimal internal force
A1 - Yan-bin SHEN
A1 - Hao-song SUN
A1 - An-dong LEI
A1 - Xiao-yuan YING
A1 - Guang YANG
A1 - Yao-zhi LUO
J0 - Journal of Zhejiang University Science A
VL - 23
IS - 9
SP - 721
EP - 732
%@ 1673-565X
Y1 - 2022
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2200003
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.
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