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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.


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.


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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