Study on temperature control of heating furnace using an improved genetic algorithm and adaptive PID

Xueqian Zuo; Jiang Han; Qiushi Li; Haisheng Diao

doi:10.1117/12.3040118

4 September 2024 Study on temperature control of heating furnace using an improved genetic algorithm and adaptive PID

Xueqian Zuo, Jiang Han, Qiushi Li, Haisheng Diao

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 132590J (2024) https://doi.org/10.1117/12.3040118
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

In the industrial production process, to address the issues of frequent manual adjustments, lengthy parameter tuning, and the challenge of selecting the best parameters in traditional PID control algorithms, this paper introduces an adaptive PID control method for heating furnace temperature control based on an improved genetic algorithm. By utilizing a chaotic algorithm to enhance the genetic algorithm's global optimization capabilities, this method achieves the optimal solution for the fitness values and identifies the optimal PID parameters for temperature control in the heating furnace. The results show that the improved genetic algorithm adaptive PID control has rapid response speed, strong anti-interference capabilities, and good robustness, thereby achieving better control effects. This method provides a theoretical basis for natural gas pre-treatment and has promising applications in engineering practice.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xueqian Zuo, Jiang Han, Qiushi Li, and Haisheng Diao "Study on temperature control of heating furnace using an improved genetic algorithm and adaptive PID", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 132590J (4 September 2024); https://doi.org/10.1117/12.3040118

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