Sintering Furnace System Identification Based on Particle Swarm Algorithm and Neural Network Control
[1]Cao Ben,Yuan Zhong,Yu Liu Hong.Sintering Furnace System Identification Based on Particle Swarm Algorithm and Neural Network Control[J].Journal of Zhengzhou University (Engineering Science),2017,38(05):39-43.[doi:10.13705/j.issn.1671-6833.2017.02.022]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38
Number of periods:
2017 05
Page number:
39-43
Column:
Public date:
2017-09-26
- Title:
- Sintering Furnace System Identification Based on Particle Swarm Algorithm and Neural Network Control
- Keywords:
-
particle swarm optimization algorithm; system identification; neural network supervisory control; PID control
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2017.02.022
- Abstract:
- During heating process of sintering furnace,the model parameters were easy to change,and traditional PID control was difficult to achieve the desired control effect.This paper used particle swarm optimization algorithm to identify the mathematical model of sintering furnace,for sintering furnace with high inertia,time-variation and strong time delay etc,a method of supervision and control based on RBF neural network,which combined PID control with neural network control.When temperature or parameters changed greatly,PID control played a major role.neural network played a regulatory role and compensated the shortage of PID control.The simulation results of MATLAB software showed that this method could improve the control precision of sintering furnace,which had a certain practicality.
- References:
- -
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