模糊神经网络锅炉温度控制系统*

doi:10.13385/j.cnki.vacuum.2021.04.14

Abstract

Abstract: A control method combined with fuzzy neural network and PID control was used to design a temperature monitoring system for modern power station boilers. The BP fuzzy neural network is used to achieve fuzzy processing of the data, and then is adjusted by the PID controller to achieve real-time temperature control. From the simulation using the Simulink software and monitoring the temperature of the power plant boilers, it is shown that the BP fuzzy neural network uses gradient descent to adjust layer by layer. The weight coefficient realizes a significant reduction of the mean square error. The fuzzy neural network PID control can speed up the system′s operation speed, improve the control accuracy, and obtain a faster response speed and a smaller amount of overshoot.

Key words: power plant boiler, back propagation, fuzzy controller, neural network, PID control, Simulink

CLC Number:

TK223

XU Li, WU Ze-ming, LIU Xu, LI hao. Boiler Temperature Control System Based on Fuzzy Neural Network[J].VACUUM, 2021, 58(4): 77-80.

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Boiler Temperature Control System Based on Fuzzy Neural Network

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