Utra-precision positioning control technique based on neural network

摘要

Due to the non-linearity behavior of the precision positioning system, an accurate mathematical control model is difficult to set up, a novel control method for ultra-precision alignment is presented. This method relies on neural network and alignment marks that are in the form of 100 mu m pitch gratings. The 0-th order Moire signals' intensity and its intensity rate are chosen as input variables of the neural network. The characteristics of the neural network make it possible to perform self-training and self-adjusting so as to achieve automatic precision alignment. A neural network model for precision positioning is set up. The model is composed of three neural layers, i. e. input layer, hidden layer and output layer. Driving signal is obtained by mapping Moire signals' intensity and its intensity rate. The experimental results show that neural network control for precision positioning can effectively improve positioning speed with high accuracy. It has the advantages of fast, stable response and good robustness. The device based on neural network can achieve the positioning accuracy of + - 0. 5 mu m.