Application of BP Neural Network PID Algorithm in Refrigerated Space Temperature Control

Wei Tian; Yi Zhun Peng; Pan Wang; Xiao Yu Wang

doi:10.4028/www.scientific.net/AMM.599-601.827

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 599-601Application of BP Neural Network PID Algorithm in...

Application of BP Neural Network PID Algorithm in Refrigerated Space Temperature Control

Abstract:

Taking the temperature control of a refrigerated space as example, this paper designs a controller which is based on traditional PID operation and BP neural network algorithm. It has better steady-state precision and adaptive ability. Firstly, the article introduces the concepts of the refrigerated space, PID and BP algorithm. Then, the temperature control of refrigerated space is simulated in MATLAB. The PID parameters will be adjusted by simulation in BP Neural Network. The PID control parameters could be created real-time online, which makes the controller performance best.

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Periodical:

Applied Mechanics and Materials (Volumes 599-601)

Pages:

827-830

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.599-601.827

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Cite this paper

Online since:

August 2014

Authors:

Wei Tian, Yi Zhun Peng*, Pan Wang, Xiao Yu Wang

Keywords:

Neural Network (NN), PID, Simulation, Temperature Control

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* - Corresponding Author

References

[1] Penghao Cui, Status and optimize the domestic cold-chain logistics, Modern Enterprise Education. Vol. 12 (2009), pp.118-119.

Google Scholar

[2] Youfeng Zhang, The Modeling and Control of A Big and Medium-sized Refrigeratory. Guangdong: Guangdong University of Technology, (2007).

Google Scholar

[3] J.A. Shaw, The PID Control Algorithm, (Process Control Solution, New York, 2003).

Google Scholar

[4] Zongxia Ning, Study on Stability of PID Control System. Xi'an: Xidian University, (2008).

Google Scholar

[5] Wang Zhaogang, The study on adaptive PID temperature control algorithm based on RBF neural network for baking furnace. Lanzhou: Lanzhou University of Technology, (2008).

Google Scholar

[6] Xueyan Zhang, Peijin Gao, and Yong Liu, The researching and simulation of BP neural Network PID controller in industry's control system. Control theory and applications. Vol. 5 (2010) pp.9-12.

Google Scholar

[7] Yan Peng, Application of PID control rule based on BPNN in greenhouse system. Journal of Agricultural Mechanization Research Vol. 6 (2011), pp.163-169.

Google Scholar

[8] Jinkun Liu, Advanced PID Control and MATLAB Simulation, (Publishing House of Electronics Industry, Beijing, 2003).

Google Scholar