DocumentCode
501123
Title
Knowledge-increasable Neural Network Group and its Control Application
Author
Lv Jin ; Fan Hai-wei ; Zhao Xiang-mo
Author_Institution
Sch. of Inf. Eng., Chang´an Univ., Xi´an, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
362
Lastpage
365
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
control system synthesis; motion control; neurocontrollers; nonlinear control systems; ships; vehicle dynamics; complex dynamic feature; compounded control structure; intelligent control structure; library-similar knowledge-increasable neural network group; online design; online identification; tracking control; uncertain nonlinear large ship; Adaptive control; Artificial intelligence; Artificial neural networks; Electronic mail; Intelligent control; Marine vehicles; Motion control; Neural networks; Nonlinear control systems; Organizing; artificial neural network; intelligence control; knowledge-increasable neural network; ship motion control;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.9
Filename
5231125
Link To Document