Resistance furnace temperature control based on prediction BP neural network

DOI

10.2991/isci-15.2015.279How to use a DOI?

Keywords

resistance furnace; BP neural network; predictive control

Abstract

For resistance furnace nonlinear, time-varying, hysteresis characteristics, the use of predictive control of advance and BP neural network has the ability to approximate any nonlinear function of the characteristics of the design of the neural network predictive controller resistance furnace temperature control. The simulation results show that this method enhances the tracking of the system, to have a good time delay compensation, accused parameter has a strong ability to adapt than traditional control methods precision, speed, excellent quality control.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yaowu Tang
PY  - 2015/01
DA  - 2015/01
TI  - Resistance furnace temperature control based on prediction BP neural network
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 2133
EP  - 2138
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.279
DO  - 10.2991/isci-15.2015.279
ID  - Tang2015/01
ER  -