Title :
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
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;
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
DOI :
10.1109/ICCSE.2009.5228538
