J4 ›› 2014, Vol. 41 ›› Issue (5): 112-117.doi: 10.3969/j.issn.1001-2400.2014.05.019

• 研究论文 • 上一篇    下一篇

采用改进鱼群算法的张拉整体结构找形方法

林敏;李团结;纪志飞   

  1. (西安电子科技大学 机电工程学院,陕西 西安  710071)
  • 收稿日期:2013-05-16 出版日期:2014-10-20 发布日期:2014-11-27
  • 通讯作者: 林敏
  • 作者简介:林敏(1984-),女,西安电子科技大学博士研究生,E-mail: structmlin@163.com.
  • 基金资助:

    国家自然科学基金资助项目(51375360)

Form-finding of tensegrity structures based on IAFSA

LIN Min;LI Tuanjie;JI Zhifei   

  1. (School of Mechano-electronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2013-05-16 Online:2014-10-20 Published:2014-11-27
  • Contact: LIN Min

摘要:

针对传统力密度法求解大规模、不规则张拉整体结构找形效率不高的问题,提出了一种力密度法与改进鱼群算法相结合的找形方法.先基于力密度法建立结构的平衡方程组, 然后采用改进的鱼群算法在力密度空间内进行全局搜索, 找出一组合适的力密度值使得平衡矩阵的秩满足求解条件, 从而找到结构的平衡构形.该算法加入了全局最优人工鱼信息, 引入了吞食行为和跳跃行为, 并采用了自适应步长, 比传统鱼群算法搜索效率更高, 不容易陷入局部极值.以扩展八面体张拉整体结构为例, 用该方法进行了找形, 并和传统鱼群算法的找形结果进行了对比分析.仿真结果表明,该找形方法的找形结果可靠, 并且收敛精度和平均最优值较传统鱼群算法均有所提高.

关键词: 张拉整体结构, 鱼群算法, 静力平衡, 找形, 群智能

Abstract:

To solve the form-finding problem of large-scale and nonregular tensegrity structures, an improved artificial fish swarm algorithm (IAFSA) is proposed on the basis of the force density formation of a tensegrity structure. First, the equilibrium equations for a tensegrity structure are developed based on the force density method. Then, a set of appropriate values of force density is found by the IAFSA in the force density space to make the rank of the equilibrium matrix satisfy the required conditions. As a consequence, the equilibrium configurations of the tensegrity structure can be derived. Furthermore, by employing the position information of the current global best artificial fish and the behaviors of swallowing and leaping of the artificial fish, the IAFSA has a higher search efficiency. Moreover, the use of leaping behaviors of the artificial fish makes the IAFSA have the ability to find global extremums. With the expandable octahedron as an example, its form-finding problem is conducted by using the IAFSA. Experimental results indicate that the form-finding results of the IAFSA are reliable. Compared with the conventional artificial fish swarm algorithm, the IAFSA has a higher convergence precision and a better average optimum value.

Key words: tensegrity structure, artificial fish swarm algorithm, static balance, form-finding, swarm intelligence

中图分类号: 

  • TP18