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  • 标题:RBF Neural Network Controller Research Based on AFSA algorithm
  • 本地全文:下载
  • 作者:Qing-kun Song ; Meng-meng Xu ; Yi Liu
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2014
  • 卷号:7
  • 期号:3
  • 页码:33-38
  • DOI:10.14257/ijhit.2014.7.3.05
  • 出版社:SERSC
  • 摘要:Artificial fish-swarm algorithm is a realization model of the swarm intelligence optimization algorithm. It uses the optimization model of imitated nature fish for feeding from top to bottom, clusters and rear, local optimization by individual fish, achieve the purpose of global optimal values highlighted in the groups. RBFNN based on the AFSA can accurately find the optimal solution quickly and ensure the diversity of artificial fish. It is easier to find the global optimal point of optimal fish. This design uses second-order pendulum as a controlled object, using artificial fish swarm algorithm applied to the neural network training algorithms, building design of RBF Neural networks control module , verifing by Matlab simulation of actual control controller performance.
  • 关键词:RBF neural network; Artificial fish-swarm algorithm; Double inverted ; pendulum
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