Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (29): 239-241.

• 工程与应用 • Previous Articles     Next Articles

Method of nonlinear systems identification with fuzzy clustering based on Takagi-Sugeno model

LI Mu1,2,LIU Zu-run2,NIAN Xiao-hong3,TAN Wen2   

  1. 1.College of Electrical and Information Engineering,Hunan University,Changsha 410082,China
    2.School of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan,Hunan 411201,China
    3.College of Information Science and Engineering,Central South University,Changsha 410083,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-10-11 Published:2007-10-11
  • Contact: LI Mu

基于T-S模型的非线性系统模糊聚类辨识方法

李 目1,2,刘祖润2,年晓红3,谭 文2   

  1. 1.湖南大学 电气与信息工程学院,长沙 410082
    2.湖南科技大学 信息与电气工程学院,湖南 湘潭 411201
    3.中南大学 信息科学与工程学院,长沙 410083
  • 通讯作者: 李 目

Abstract: A method of nonlinear systems identification with fuzzy clustering based on T-S model has been proposed in this paper.In T-S fuzzy model the premise and conclusion have been identified separately,since have simplified the steps of the identification,and then have improved the generalization ability,also have resolved the system problem of the complicated degree exaltation but the rule few aggrandizement.Finally,the effectiveness of the propose method has been demonstrated by identification of the nonlinear systems.

摘要: 提出一种基于T-S模型的非线性系统模糊聚类辨识方法,对T-S模糊模型的前提部分和结论部分进行分开辨识,既简化该模型的辨识步骤,又提高它的泛化能力,同时也解决了T-S模糊模型随辨识系统复杂程度提高而规则数增大的问题。对一个非线性系统辨识的仿真结果验证了这种模糊聚类辨识方法的有效性。