基于遗传算法的复杂自适应结构设计

S. Bland, Lizeng Sheng, R. Kapania
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引用次数: 4

摘要

遗传算法(GAs)由于能够解决其他方法难以解决的大型复杂优化问题而越来越受欢迎。本文介绍了GAs的理论及其算子。简要介绍了气体发生器在航空航天工程中的应用研究现状。在前人工作的基础上,讨论了空间望远镜反射镜中压电作动器的最佳位置。这里讨论的问题涉及从最多193个候选位置中选择15个压电致动器的最佳位置和最佳电压。结果表明,遗传算法具有较好的鲁棒性和有效性,可得到8.4*1021个以上的可能解。针对多准则优化问题,给出了两组执行机构布置方案。本文还介绍了用气相函数进行连续梁集中损伤的结构损伤检测的反问题。找到了一种实数编码遗传算法,为这一损伤检测问题提供了相对准确的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of complex adaptive structures using the genetic algorithm
Genetic algorithms (GAs) are becoming increasingly popular due to their ability to solve large complex optimization problems which other methods have difficulty solving. In this paper, an introduction to the theory of GAs and its operators are presented. A brief overview of the current research using GAs in aerospace engineering applications is given. Based on the author's previous work, optimal piezoelectric actuator placement for space telescope mirrors using GAs is discussed. The problem discussed here involves finding optimal locations and optimal voltages for 15 piezoelectric actuators, selected from a maximum of 193 candidate locations. The GA was found to be effective and robust in solving this problem with more than 8.4*1021 possible solutions. Two sets of actuator placements are given as solutions to the multi-criteria optimization problem. The use of GAs for structural damage detection inverse problems for concentrated damage of a continuous beam is also shown. A real number encoded GA was found to provide relatively accurate solutions for this damage detection problem.
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