The Research and Application of the PID Controller Based on the Improved BP Network

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Abstract:

This paper mainly introduces a PID controller, which is optimized by an improved BP algorithm, and discusses the analysis method of it. It states a way to dynamically adjust the learning rate and the momentum factor through the variety of the input and output of the PID controller to realize an intelligent control. And it connects this control method with the control of the hot winds of the gas in bar furnace of a steel plant to realize a closed-loop control and solve the problems such as the wave of the gas pressure and the insufficiency of combustion. According to the practice, the fluctuation of gas pressure is restricted within 5%, which means that this control method could largely improve the precision of furnace control and further more raise the economic and social benefits.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

2726-2731

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Online since:

June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Weiheng,Yan Wang,The combustion control method research of gas heating furnace . Thermal Power Engineering. 2010. 05. In Chinese.

Google Scholar

[2] JinkunLiu , Intelligent control, Electronic Industry Press, 2005. 5. In Chinese.

Google Scholar

[3] Youling Yao, Intelligent Adaptive Decoupling Control and its Application in Integrated Control of Modernized Strip Flatness and Gauge, 2007. 10. In Chinese.

Google Scholar

[4] JinlingShan , Caiwen Ma , The PID controller Based on the BP neural network, ActaPhotonica Sinica. 2005. 5. In Chinese.

Google Scholar

[5] ChunshanShi, Guoshan Zhang,The method research of the PID control based on the improved BP neural network. Computer simulation. 2006. 23(12). In chinese.

Google Scholar

[6] Di Liu, YonghongTang. The algorithm of the PID control based on the improved BP neural network. Ordnance Industry Automation. 2010. 29(3). In Chinese.

Google Scholar