Journal of Robotics, Networking and Artificial Life

Volume 5, Issue 1, June 2018, Pages 63 - 66

Simulation of Main Steam Temperature Control System Based on Neural Network

Authors
Fengzhi Daidaifz@tust.edu.cn, Yujie Yan, Baochang Wei, Yuxing Ouyang, Lingran An
College of Electronic Information and Automation, Tianjin University of Science and Technology, China;
Available Online 30 June 2018.
DOI
10.2991/jrnal.2018.5.1.14How to use a DOI?
Keywords
BP neural network; PID control; MATLAB; temperature
Abstract

This paper designs a PID control system based on the BP neural network. The control system can adjust three adjustable parameters of PID controller through BP neural network algorithm. The main steam temperature control system of the thermal power plant was taken as the object, and simulation analysis was performed through MATLAB. The experimental results show that the design scheme has good performance and anti-interference ability, and has certain practicability to the main steam temperature control system of thermal power plant.

Copyright
Copyright © 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
5 - 1
Pages
63 - 66
Publication Date
2018/06/30
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.2018.5.1.14How to use a DOI?
Copyright
Copyright © 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Fengzhi Dai
AU  - Yujie Yan
AU  - Baochang Wei
AU  - Yuxing Ouyang
AU  - Lingran An
PY  - 2018
DA  - 2018/06/30
TI  - Simulation of Main Steam Temperature Control System Based on Neural Network
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 63
EP  - 66
VL  - 5
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2018.5.1.14
DO  - 10.2991/jrnal.2018.5.1.14
ID  - Dai2018
ER  -