Nonlinear system identification based on ANFIS

被引：0
|
作者：
Hou, ZX [1 ]
Shen, QT [1 ]
Li, HQ [1 ]
机构：
[1] Cent S Univ, Coll Informat Sci & Engn, Changsha 410083, Peoples R China
来源：
PROCEEDINGS OF 2003 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS & SIGNAL PROCESSING, PROCEEDINGS, VOLS 1 AND 2 | 2003年
关键词：
ANFIS; nonlinear system; identification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
System identification is the basis of designing control system, and it is very difficulty to identify the nonlinear system today. A method of fuzzy identification had been provided in reference 1, and another method of using neural networks to identify system had been provided in reference 2;In this paper, Author points out the disadvantages of those methods and a new identification method based adaptive neural-fuzzy inference system (ANFIS) is provided, as assembles the advantages of fuzzy theory and neural networks. The structure and algorithms of ANFIS is designed firstly, then a nonlinear function is tested using the method, and the simulation results show that ANFIS is very effective to identify the nonlinear system.
引用
收藏
页码：510 / 512
页数：3
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