Title :
Self-adaptive modeling method based on T-S fuzzy RBF NN and its application
Author :
Li, Lina ; Yang, Yang
Author_Institution :
Coll. of Phys., LiaoNing Univ., Shenyang, China
Abstract :
For the complex nonlinear systems, a self-adaptive modeling method based on T-S fuzzy RBF NN is introduced in this paper, in which online fuzzy clustering and improved PSO algorithms are used to implement the structure identification and parameter identification of the network. After theory analysis, the corresponding computer simulation was done to confirm the effectiveness and superiority of the method mentioned in this paper, and to provide a reference for practical application of this method.
Keywords :
adaptive systems; nonlinear systems; parameter estimation; particle swarm optimisation; pattern clustering; radial basis function networks; PSO algorithms; T-S fuzzy RBF NN; computer simulation; network parameter identification; network structure identification; nonlinear systems; online fuzzy clustering; self-adaptive modeling; Clustering algorithms; Current density; RBF NN; T-S fuzzy model; gradient descent algorithm; improved PSO algorithm; online fuzzy clustering;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579638
