Research on the design of the ultra-high-precision positioning control error compensation

2016 ◽  
Vol 17 (10) ◽  
pp. 1351-1358 ◽  
Author(s):  
Dae-Kwang Park ◽  
Gyung-Il Lee ◽  
Jia-Chen Gao ◽  
Jae-Yeol Kim
Keyword(s):  
High Precision ◽  
Error Compensation ◽  
Precision Positioning ◽  
Control Error ◽  
Positioning Control

A High Precision Positioning Control Method Based on Learning Algorithm with Reference Model

2011 ◽  
Vol 211-212 ◽  
pp. 671-675
Author(s):  
Kenji Nakajima ◽  
Hiroyuki Saitou ◽  
Seiji Hashimoto
Keyword(s):  
Neural Network ◽  
High Precision ◽  
Control Method ◽  
Reference Model ◽  
Learning Algorithm ◽  
Input Saturation ◽  
Control Input ◽  
Precision Positioning ◽  
Positioning Control ◽  
The Neural Network

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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