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
         
        
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
         
        
            Conference_Location : 
Wuhan
         
        
            Print_ISBN : 
978-0-7695-3645-3
         
        
        
            DOI : 
10.1109/CINC.2009.9