Temperature control of thermal storage electric boiler based on fuzzy neural network

Guan-jun Song; Jing-xia Liu; Meng-ting Wang

doi:10.1117/12.2640940

2 December 2022 Temperature control of thermal storage electric boiler based on fuzzy neural network

Guan-jun Song, Jing-xia Liu, Meng-ting Wang

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 122882D (2022) https://doi.org/10.1117/12.2640940
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Through the research on the temperature control system of the solid regenerative electric boiler, it is known that it has great limitations in terms of overshoot, control accuracy, and required adjustment time. In order to better improve it Based on the traditional PID algorithm, using advanced fuzzy control principles and strong learning ability of neural network, it is proposed to use fuzzy neural network PID controller to optimize temperature control to improve the accuracy and speed of temperature adjustment.This paper introduces the basic structure and principle of solid regenerative electric boiler, and proposes a fuzzy neural network PID algorithm for temperature control of solid regenerative electric boiler. To set up the conventional PID and the indistinct nervous network PID control model by means of the application of emulation. The summing-up is drawn: the indistinct nervous network PID controller has smaller overshoot and faster response in contrary to the conventional. In the case of interference, the anti-interference ability is more ideal.

Citation Download Citation

Guan-jun Song, Jing-xia Liu, and Meng-ting Wang "Temperature control of thermal storage electric boiler based on fuzzy neural network", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 122882D (2 December 2022); https://doi.org/10.1117/12.2640940

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