Title : 
Neural-network cross-coupled control system with application on circular tracking of linear motor X-Y table
         
        
            Author : 
Wang, Gou-Jen ; Lee, Tzong-Jing
         
        
            Author_Institution : 
Dept. of Mech. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan
         
        
        
        
        
        
            Abstract : 
In this article a new neural-network based cross-coupled control algorithm that integrates the cross-coupled control and neural network techniques together is presented In this neural network based cross-coupled control system, fixed gain PID controller for each individual axis is replaced by a heuristic neural network learning controller. The conventional cross-coupled controller is substituted by an efficient neural network cross-coupled controller. Experimental results show that the proposed new neural network based cross-coupled control scheme can be successfully applied to the precise circular tracking problem of a nonlinear uncertain linear motor X-Y table. It is also demonstrated that performance of the neural network based cross-coupled control scheme is superior to the conventional cross-coupled control scheme
         
        
            Keywords : 
heuristic programming; linear motors; neurocontrollers; position control; tracking; circular tracking; heuristic neural network learning controller; neural-network cross-coupled control algorithm; nonlinear uncertain linear motor X-Y table; Control systems; Electrical equipment industry; Error correction; Motion control; Neural networks; Nonlinear control systems; Servomechanisms; Servomotors; Three-term control; Uncertainty;
         
        
        
        
            Conference_Titel : 
Neural Networks, 1999. IJCNN '99. International Joint Conference on
         
        
            Conference_Location : 
Washington, DC
         
        
        
            Print_ISBN : 
0-7803-5529-6
         
        
        
            DOI : 
10.1109/IJCNN.1999.832729