›› 2015, Vol. 28 ›› Issue (11): 16-.

• 论文 • 上一篇    下一篇



  1. (上海理工大学 光电信息与计算机工程学院,上海 200093)
  • 出版日期:2015-11-15 发布日期:2015-12-15
  • 作者简介:董新燕(1990—),女,硕士研究生。研究方向:系统辨识,智能控制。E-mail:1163574752@qq.com
  • 基金资助:


T S Model Identification Based on an Improved Gravitational Search Algorithm

DONG Xinyan,DING Xueming,WANG Jian   

  1. (School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
  • Online:2015-11-15 Published:2015-12-15



关键词: T S模型辨识, 基因突变, FCM聚类, 引力搜索算法


As the gravitational search algorithm plays a negative influence on the search accuracy of the complex issues,especially the poor search quality of standard Gravitational Search Algorithm(GSA) in the high dimensional function optimization,it is easy to get into premature convergence in the optimization process.An improved gravitational search algorithm based on genetic mutations(gmGSA) is proposed to identify the parameter of T-S model.An improved fuzzy c-means(FCM) based on simulated annealing(SA) and genetic algorithm(GA),denote as SAGA-FCM,is also proposed to identify the structure of T-S model.The simulation results show the proposed methods can effectively obtain compact and accurate fuzzy models with excellent capability of generalization.

Key words: identification of T S model;genetic mutations;FCM clustering;gravitational search algorithm


  • TP273.4