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Parameters Optimization of the Heating Furnace Control Systems Based on BP Neural Network Improved by Genetic Algorithm

Qiong Wang*, Xiaokan Wang
Henan Mechanical and Electrical Vocational College, Zhengzhou, 451191, China
* Corresponding Author: Qiong Wang. Email:

Journal on Internet of Things 2020, 2(2), 75-80. https://doi.org/10.32604/jiot.2020.010226

Received 01 January 2020; Accepted 05 May 2020; Issue published 14 September 2020

Abstract

The heating technological requirement of the conventional PID control is difficult to guarantee which based on the precise mathematical model, because the heating furnace for heating treatment with the big inertia, the pure time delay and nonlinear time-varying. Proposed one kind optimized variable method of PID controller based on the genetic algorithm with improved BP network that better realized the completely automatic intelligent control of the entire thermal process than the classics critical purporting (Z-N) method. A heating furnace for the object was simulated with MATLAB, simulation results show that the control system has the quicker response characteristic, the better dynamic characteristic and the quite stronger robustness, which has some promotional value for the control of industrial furnace.

Keywords

Genetic algorithm; parameter optimization; PID control; BP neural network; heating furnace

Cite This Article

Q. Wang and X. Wang, "Parameters optimization of the heating furnace control systems based on bp neural network improved by genetic algorithm," Journal on Internet of Things, vol. 2, no.2, pp. 75–80, 2020.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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