A Fuzzy Neural Networks Controller of Underwater Vehicles Based on Ant Colony Algorithm

被引：3

作者：

Tang Xudong ^{[1
]}

Pang Yongjie ^{[1
]}

Li Ye ^{[1
]}

Qing Zaibai ^{[1
]}

机构：

[1] Harbin Engn Univ, Key Lab Autonomous Underwater Vehicle, Harbin 150001, Peoples R China

来源：

Proceedings of the 27th Chinese Control Conference, Vol 4 | 2008年

关键词：

Autonomous Underwater Vehicles; Fuzzy Neural Network Control; Expert Experience; Ant Colony Algorithm;

D O I：

10.1109/CHICC.2008.4604986

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Owing to the characteristic of autonomous underwater vehicles (AUV) control and to solve the typical nonlinearity control system, we deduced a new fuzzy neual network control based on expert experience and ant colony algorithm. This algorithm-superiority in solving combination optimization problems which consists of the rule sets and parameters of the membership functions of the continuous fuzzy controller to be slected. In order to enhance the efficiency of ant colony algorithm and prevent the precocity, the expert experience and improving ant colony algorithm are introduced in. Simulation results and applications showed that method,is effective enough to make control simpler and robust and to get good control performance.

引用

页码：637 / 641

页数：5

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