Position control of ball and plate system based on ANFIS

被引：0
|
作者：
Bai, Ming [1 ]
Tian, Yantao [1 ]
Su, Jintao [1 ]
机构：
[1] Jilin Univ, Coll Commun Engn, Changchun 130025, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
An adaptive neural-fuzzy controller was proposed for a ball and plate laboratory setup. The adaptive learning mechanism made the fuzzy system to adapt to the intrinsically nonlinear characteristic of the model. Because the back propagation (BP) learning algorithm was slow and easy to fall into local minimum, we introduced the improved BP algorithm with momentum item to train weights of network. When compared with traditional TS type fuzzy control, as expected, this control strategy behaved excellent robust and good dynamic characteristics. The simulation result showed that adaptive neural fuzzy inference system (ANFIS) was feasible. It is a valid control scheme for nonlinear dynamic system.
引用
收藏
页码：165 / 168
页数：4
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