scholarly journals High Precision Positioning Control to Reference Input Given as Periodic Functions of Rotational Angle to Spindle.

1993 ◽  
Vol 113 (1) ◽  
pp. 79-86 ◽  
Author(s):  
Jin-Hua She ◽  
Michio Nakano
2011 ◽  
Vol 211-212 ◽  
pp. 671-675
Author(s):  
Kenji Nakajima ◽  
Hiroyuki Saitou ◽  
Seiji Hashimoto

In this paper, a high precision positioning control method based on the learning algorithm with the reference model is proposed. The reference model is composed of a plant model and a feedback controller. In the proposed control method, disturbance, modeling error and nonlinear characteristic can be effectively compensated by the neural network-based controller, which learns the reference model. Moreover, the control-input saturation problem due to the over-learning for the neural network can be avoided. The effectiveness of the proposed control method is experimentally verified using the precision positioning equipment with nonlinear friction characteristics.


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