Research of intelligence control based on Knowledge-increasable Neural Network Group

Author

Lv, Jin ; Zhao, Xiang-Mo ; Guo Chen

Author_Institution

Sch. of Inf. Eng., Chang´´an Univ., Xi´´an, China

fYear

2009

fDate

25-28 July 2009

Firstpage

3

Lastpage

6

Abstract

Aiming at the complex dynamic feature of large ship, an intelligent control structure based on library-similar knowledge-increasable neural network group is presented. This compounded control structure using the dynamic knowledge-increasable learning capability of the neural network groups, solve the problems of online identification and online design of the controller, so that the high precise output tracking control of uncertain nonlinear large ship can be realized. Simulating results show that it is feasible and effective.

Keywords

learning (artificial intelligence); marine systems; motion control; neurocontrollers; ships; compounded control structure; intelligent control structure; knowledge-increasable learning capability; knowledge-increasable neural network group; online identification; output tracking control; ship motion control; simulation result; Artificial neural networks; Automatic control; Electronic mail; Intelligent control; Intelligent networks; Knowledge engineering; Marine vehicles; Motion control; Neural networks; Nonlinear control systems; artificial neural network; intelligence control; knowledge-increasable neural network; ship motion control;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education, 2009. ICCSE '09. 4th International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-3520-3

Electronic_ISBN

978-1-4244-3521-0

Type

conf

DOI

10.1109/ICCSE.2009.5228538

Filename

5228538