A fuzzy neural networks controller of underwater vehicles based on ant colony algorithm

Author

Xudong, Tang ; Yongjie, Pang ; Ye, Li ; Zaibai, Qing

Author_Institution

Key Lab. of Autonomous Underwater Vehicle, Harbin Eng. Univ., Harbin

fYear

2008

fDate

16-18 July 2008

Firstpage

637

Lastpage

641

Abstract

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.

Keywords

continuous systems; fuzzy neural nets; neurocontrollers; nonlinear control systems; optimisation; remotely operated vehicles; underwater vehicles; ant colony algorithm; autonomous underwater vehicles control; combination optimization problems; continuous fuzzy controller; fuzzy neural networks controller; nonlinearity control system; Ant colony optimization; Automotive engineering; Control systems; Electronic mail; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Nonlinear control systems; Underwater vehicles; Ant Colony Algorithm; Autonomous Underwater Vehicles; Expert Experience; Fuzzy Neural Network Control;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2008. CCC 2008. 27th Chinese

Conference_Location

Kunming

Print_ISBN

978-7-900719-70-6

Electronic_ISBN

978-7-900719-70-6

Type

conf

DOI

10.1109/CHICC.2008.4604986

Filename

4604986