The Optimal Placement about Actuators of Active Structural Control Based on Genetic Algorithm

MAO Keyang; SUN Zuoyu; YAN Lewei; WANG Hui

您当前的位置：

首页 >

文章列表页 >

The Optimal Placement about Actuators of Active Structural Control Based on Genetic Algorithm

更新时间：2023-12-11

- The Optimal Placement about Actuators of Active Structural Control Based on Genetic Algorithm
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 52, Issue 2, Pages: 129-132(2013)
- 作者机构：
  
  广州大学土木工程学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013，
  
  Published Online：25 March 2013，
扫描看全文
MAO Keyang, SUN Zuoyu, YAN Lewei, et al. The Optimal Placement about Actuators of Active Structural Control Based on Genetic Algorithm. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 52(2):129-132(2013)
DOI：

MAO Keyang, SUN Zuoyu, YAN Lewei, et al. The Optimal Placement about Actuators of Active Structural Control Based on Genetic Algorithm. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 52(2):129-132(2013) DOI：

摘要

研究地震激励作用下主动控制结构的作动器优化布置，基于等效激励法构造了随机激励，应用状态空间控制算法进行了求解。针对作动器优化布置问题提出了基于遗传算法的优化方案，即利用遗传算法的0

1染色体编码模拟作动器的楼层空间布置，实现了作动器数目限定条件下，以楼层最大加速度和层间位移角组合为控制目标函数的作动器最优布置。仿真分析表明，该优化方法适应性强，效果显著。

Abstract

The optimization of actuators of an active control structure under seismic excitation is studied. The random excitation is generated by equivalent excitation method

and the state space control algorithm is employed to calculate the dynamic responses. An optimized procedure based on genetic algorithm is proposed

in which a 0-1 chromosome coding is used to resemble the spatial arrangement of actuators. Several typical cases are analyzed

in which the fitness objectives are composed of maximum acceleration response and maximum inter-story angle

while the structure is controlled by certain actuators. The results demonstrate that the proposed method is suitable and effective.

关键词

状态空间控制等效激励法遗传算法作动器优化布置

Keywords

state space controlequivalent excitation methodgenetic algorithmoptimization of actuators.

references

Views

443

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Location routing problem with outsourcing strategy

Optimization of Bridges- Parameters Based on BP Neural Network and Genetic Algorithm

Solving Nonlinear Equations Based on Improved Genetic Algorithm

Prediction Model based on Particle Swarm-projection Pursuit and Genetic-neural Networks

Optimal Two-stage Fuzzy Control for Urban Traffic Signals at #br# Isolated Intersection and Its Simulation

Related Author

ZHU Zixuan

WU Weitiao

LI Ting

JIN Wenzhou

HUANG Xiaoqing

HE Qinghui

TANG Liqun

XI Huifeng

Related Institution

School of Civil and Transportation Engineering, South China University of Technology

School of Construction Engineering Maoming University



School of Building and Communication South China University of Techenology

广州大学工程力学系

Postal code：510275
Tel：020-84112585，84113223 Email：xuebaozr@mail.sysu.edu.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰