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

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 gr...

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Bibliographic Details
Published in:Journal of Zhejiang University. A. Science Vol. 23; no. 9; pp. 721 - 732
Main Authors: Shen, Yan-bin, Sun, Hao-song, Lei, An-dong, Ying, Xiao-yuan, Yang, Guang, Luo, Yao-zhi
Format: Journal Article
Language:English
Published: Hangzhou Zhejiang University Press 01.09.2022
Springer Nature B.V
China State Construction Engineering(Hong Kong)Limited,Hong Kong 999077,China
College of Civil Engineering and Architecture,Zhejiang University,Hangzhou 310058,China%College of Civil Engineering and Architecture,Zhejiang University,Hangzhou 310058,China
Subjects:
Actuators
Adaptive algorithms
Adaptive control
Algorithms
Civil Engineering
Classical and Continuum Physics
Control methods
Engineering
Environmental changes
Environmental conditions
Genetic algorithms
Global optimization
Industrial Chemistry/Chemical Engineering
Internal forces
Mechanical Engineering
Objective function
Optimization models
Research Article
Smart structures
Strings
Struts
Adaptive structure
梯度遗传算法
Grillage adaptive beam string structure (GABSS)
Gradient—genetic algorithm (GGA)
Structural control
结构控制
作动器
交叉张弦梁结构
Actuator
自适应结构
Gradient–genetic algorithm (GGA)
ISSN:1673-565X, 1862-1775
Online Access:Get full text
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Summary: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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ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.A2200003