Title :
Research of intelligence control based on Library-similar Knowledge-increasable Neural Network Group
Author :
Jin Lv ; Xiang-mo Zhao
Author_Institution :
Sch. of Inf. Eng., Changan Univ., Xian, 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 :
adaptive control; control system synthesis; motion control; neurocontrollers; nonlinear control systems; ships; tracking; uncertain systems; adaptive control structure; intelligence control; library similar knowledge increasable neural network group; online controller design; output tracking control; ship dynamic feature; ship motion control; uncertain nonlinear large ship; Artificial neural networks; Automatic control; Automation; 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 :
Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3817-4
DOI :
10.1109/ICIMA.2009.5156546
