@inproceedings{2c1b691d3f8642d3896f864385e56562,
title = "Adaptive ANN modeling of proportional valve based on data classification",
abstract = "This paper aims at controlling the nonlinear couple variables voltage and flow precisely in the electro-hydraulic proportional. A static model of voltage, pressure and flow, which is established from BP neural network based on data classification, is presented. The data classification principle is given based on dead zone and hysteresis which may cause the low accuracy of model. The experimental results and applications show that the modeling can reflect the characteristics of electro-hydraulic proportional and achieve high precision in pressure controlling. What is more, Depending on real time online parameters tuning, it can improve the model accuracy and control precision.",
keywords = "Adaption, BP neural network, Data classification, Electro-hydraulic proportional, Nonlinear modeling",
author = "Qiao Xiao and Shoukun Wang and Junzheng Wang",
year = "2010",
language = "English",
isbn = "9787894631046",
series = "Proceedings of the 29th Chinese Control Conference, CCC'10",
pages = "1352--1357",
booktitle = "Proceedings of the 29th Chinese Control Conference, CCC'10",
note = "29th Chinese Control Conference, CCC'10 ; Conference date: 29-07-2010 Through 31-07-2010",
}