Fuzzy Neural Network Hybrid Learning Control on AUV

被引：0

作者：

Zhao, Jing ^{[1
]}

Han, Zhaolin ^{[1
]}

Fang, Yuanyuan ^{[1
]}

机构：

[1] Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China

来源：

AUTOMATION EQUIPMENT AND SYSTEMS, PTS 1-4 | 2012年 / 468-471卷

关键词：

Autonomous Underwater Vehicle; Fuzzy Neural Network; Immune Genetic Algorithm; B-spline Function;

D O I：

10.4028/www.scientific.net/AMR.468-471.1732

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A novel controller based on the fuzzy B-spline neural network is presented, which combines the advantages of qualitative defining capability of fuzzy logic, quantitative learning ability of neural networks and excellent local controlling ability of B-spline basis functions, which are being used as fuzzy functions. A hybrid learning algorithm of the controller is proposed as well. The results show that it is feasible to design the fuzzy neural network control of autonomous underwater vehicle by the hybrid learning algorithm.

引用

页码：1732 / 1735

页数：4

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